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Liu Y, De Mulatier S, Matsuhisa N. Unperceivable Designs of Wearable Electronics. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2025:e2502727. [PMID: 40317616 DOI: 10.1002/adma.202502727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2025] [Revised: 03/29/2025] [Indexed: 05/07/2025]
Abstract
Wearable smart electronics are taking an increasing part of the consumer electronics market, with applications in advanced healthcare systems, entertainment, and Internet of Things. The advanced development of flexible, stretchable, and breathable electronic materials has paved the way to comfortable and long-term wearables. However, these devices can affect the wearer's appearance and draw attention during use, which may impact the wearer's confidence and social interactions, making them difficult to wear on a daily basis. Apart from comfort, one key condition for user acceptance is that these new technologies seamlessly integrate into our daily lives, remaining unperceivable to others. In this review, strategies to minimize the visual impact of wearable devices and make them more suitable for daily use are discussed. These new devices focus on being unperceivable when worn and comfortable enough that users almost forget their presence, reducing psychological discomfort while maintaining accuracy in signal collection. Materials selection is crucial for developing long-term and unperceivable wearable devices. Recent developments in these unperceivable electronic devices are also covered, including sensors, transistors, and displays, and mechanisms to achieve unperceivability are discussed. Finally, the potential applications are summarized and the remaining challenges and prospects are discussed.
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Affiliation(s)
- Yijun Liu
- Research Center for Advanced Science and Technology (RCAST), The University of Tokyo, Tokyo, 1538904, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, 1538505, Japan
| | - Séverine De Mulatier
- Research Center for Advanced Science and Technology (RCAST), The University of Tokyo, Tokyo, 1538904, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, 1538505, Japan
- LIMMS/CNRS, Institute of Industrial Science, The University of Tokyo, Tokyo, 1538505, Japan
| | - Naoji Matsuhisa
- Research Center for Advanced Science and Technology (RCAST), The University of Tokyo, Tokyo, 1538904, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, 1538505, Japan
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2
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Yu X, Luo Z, Ouyang X, Wang W, Rao Y, Yuan Y, Cai Z, Hu Y, Xiang L. Highly Stable Polymeric Electrooculography Electrodes for Contactless Human-Machine Interactions. ACS Sens 2025; 10:3013-3022. [PMID: 40203133 DOI: 10.1021/acssensors.5c00031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2025]
Abstract
Capturing the electrooculography (EOG) signals is very attractive for assistive devices and user interfaces for virtual reality (VR) systems. However, the current EOG acquisition systems face challenges in ensuring user comfort, particularly in terms of electrode electrical and mechanical performance, long-term usability, thermal effects, and overall system portability. This study presents polymeric dry flexible electrodes, composed of a composite of poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS), poly(vinyl alcohol) (PVA), Gallic acid (GA), and D-sorbitol, forming a dynamic cross-linked network that ensures strong adhesion, stretchability, and electrical stability. These electrodes maintain their performance for up to 72 h, and can be restored through heat reactivation if performance degrades after prolonged storage. This electrode exhibits excellent biocompatibility, causing no skin irritation or thermal effects with continuous use. We have also developed a flexible circuit for real-time signal processing and wireless transmission, which operates in coordination with the EOG electrodes. The system employs a convolutional neural network (CNN) to achieve a 97.1% accuracy in classifying various eye movement patterns. The system enables contactless control of digital interfaces through simple eye movements, offering a solution for long-term, comfortable, and high-fidelity EOG-based human-machine interfaces, particularly for VR integration and assistive technologies for individuals with disabilities.
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Affiliation(s)
- Xingge Yu
- College of Materials Science and Engineering, Hunan University, Changsha 410082, China
| | - Zebang Luo
- College of Materials Science and Engineering, Hunan University, Changsha 410082, China
| | - Xilin Ouyang
- College of Materials Science and Engineering, Hunan University, Changsha 410082, China
| | - Wenqiang Wang
- College of Materials Science and Engineering, Hunan University, Changsha 410082, China
| | - Yuxuan Rao
- Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan 411105, China
| | - Yulong Yuan
- Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan 411105, China
| | - Zhenpeng Cai
- Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan 411105, China
| | - Youfan Hu
- Key Laboratory for the Physics and Chemistry of Nanodevices, Center for Carbon-Based Electronics and School of Electronics, Peking University, Beijing 100871, China
- Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan 411105, China
| | - Li Xiang
- College of Materials Science and Engineering, Hunan University, Changsha 410082, China
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Linh VTN, Han S, Koh E, Kim S, Jung HS, Koo J. Advances in wearable electronics for monitoring human organs: Bridging external and internal health assessments. Biomaterials 2025; 314:122865. [PMID: 39357153 DOI: 10.1016/j.biomaterials.2024.122865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 09/06/2024] [Accepted: 09/26/2024] [Indexed: 10/04/2024]
Abstract
Devices used for diagnosing disease are often large, expensive, and require operation by trained professionals, which can result in delayed diagnosis and missed opportunities for timely treatment. However, wearable devices are being recognized as a new approach to overcoming these difficulties, as they are small, affordable, and easy to use. Recent advancements in wearable technology have made monitoring information possible from the surface of organs like the skin and eyes, enabling accurate diagnosis of the user's internal status. In this review, we categorize the body's organs into external (e.g., eyes, oral cavity, neck, and skin) and internal (e.g., heart, brain, lung, stomach, and bladder) organ systems and introduce recent developments in the materials and designs of wearable electronics, including electrochemical and electrophysiological sensors applied to each organ system. Further, we explore recent innovations in wearable electronics for monitoring of deep internal organs, such as the heart, brain, and nervous system, using ultrasound, electrical impedance tomography, and temporal interference stimulation. The review also addresses the current challenges in wearable technology and explores future directions to enhance the effectiveness and applicability of these devices in medical diagnostics. This paper establishes a framework for correlating the design and functionality of wearable electronics with the physiological characteristics and requirements of various organ systems.
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Affiliation(s)
- Vo Thi Nhat Linh
- Advanced Bio and Healthcare Materials Research Division, Korea Institute of Materials Science (KIMS), Changwon, 51508, South Korea
| | - Seunghun Han
- School of Biomedical Engineering, College of Health Science, Korea University, Seoul, 02841, South Korea; Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, South Korea
| | - Eunhye Koh
- Advanced Bio and Healthcare Materials Research Division, Korea Institute of Materials Science (KIMS), Changwon, 51508, South Korea
| | - Sumin Kim
- School of Biomedical Engineering, College of Health Science, Korea University, Seoul, 02841, South Korea; Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, South Korea
| | - Ho Sang Jung
- Advanced Bio and Healthcare Materials Research Division, Korea Institute of Materials Science (KIMS), Changwon, 51508, South Korea; Advanced Materials Engineering, University of Science and Technology (UST), Daejeon, 34113, South Korea; School of Convergence Science and Technology, Medical Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, South Korea.
| | - Jahyun Koo
- School of Biomedical Engineering, College of Health Science, Korea University, Seoul, 02841, South Korea; Interdisciplinary Program in Precision Public Health, Korea University, Seoul, 02841, South Korea.
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Yang H, Guo Q, Chen G, Zhao Y, Shi M, Zhou N, Huang C, Mao H. An intelligent humidity sensing system for human behavior recognition. MICROSYSTEMS & NANOENGINEERING 2025; 11:17. [PMID: 39837819 PMCID: PMC11751383 DOI: 10.1038/s41378-024-00863-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2024] [Revised: 11/26/2024] [Accepted: 12/20/2024] [Indexed: 01/23/2025]
Abstract
An intelligent humidity sensing system has been developed for real-time monitoring of human behaviors through respiration detection. The key component of this system is a humidity sensor that integrates a thermistor and a micro-heater. This sensor employs porous nanoforests as its sensing material, achieving a sensitivity of 0.56 pF/%RH within a range of 60-90% RH, along with excellent long-term stability and superior gas selectivity. The micro-heater in the device provides a high operating temperature, enhancing sensitivity by 5.8 times. This significant improvement enables the capture of weak humidity variations in exhaled gases, while the thermistor continuously monitors the sensor's temperature during use and provides crucial temperature information related to respiration. With the assistance of a machine learning algorithm, a behavior recognition system based on the humidity sensor has been constructed, enabling behavior states to be classified and identified with an accuracy of up to 96.2%. This simple yet intelligent method holds great potential for widespread applications in medical assistance analysis and daily health monitoring.
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Affiliation(s)
- Huabin Yang
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Qiming Guo
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Guidong Chen
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- BYD Auto Industry Company Limited, Shenzhen, 518118, China
| | - Yuefang Zhao
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Meng Shi
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Na Zhou
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China.
- University of Chinese Academy of Sciences, Beijing, 101408, China.
| | - Chengjun Huang
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China
- University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Haiyang Mao
- Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, 100029, China.
- University of Chinese Academy of Sciences, Beijing, 101408, China.
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Kwon Y, Kim J, Kim H, Kang TW, Lee J, Jang SS, Lee Y, Yeo WH. Printed Nanomaterials for All-in-One Integrated Flexible Wearables and Bioelectronics. ACS APPLIED MATERIALS & INTERFACES 2024; 16:68016-68026. [PMID: 39586587 DOI: 10.1021/acsami.4c17939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/27/2024]
Abstract
Recent advancements in printing technologies allow for fabricating various wearable sensors, circuits, and integrated electronics. However, most printing tools have limited ranges of handling ink viscosity, a short working distance, and a limited feature size for developing sophisticated electronics. Here, this paper introduces an all-in-one integrated wearable electronic system via multilayer, multinanomaterial printing. Versatile, high-resolution aerosol-jet printing could successfully print Cu nanoparticles, Ag nanoparticles, PEDOT:PSS, and polyimide (PI) to manufacture nanomembrane composite structures, including skin-contact electrodes and wireless circuits. The printed polymer, PEDOT:PSS deposited on the Cu, ensures biocompatibility when making direct skin contact while enhancing electrical conductivity for electrodes. A self-assembled monolayer facilitates better adhesion of Cu nanoparticles on the PI. Also, using intensive pulsed light, a photonic sintering method minimizes Cu-oxidation while avoiding thermal damage. The combined experimental and computational study shows the mechanical flexibility and reliability of the printed integrated device. With human subjects, the flexible wireless bioelectronic system demonstrates superior performance in detecting high-fidelity physiological signals on the skin, including electromyograms, electrooculograms, electrocardiograms, and motions, proving its potential applications in portable human healthcare and persistent human-machine interfaces.
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Affiliation(s)
- Youngjin Kwon
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Jongsu Kim
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Hojoong Kim
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Korea KIAT-Georgia Tech Semiconductor Electronics Center (K-GTSEC), Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Tae Woog Kang
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Jimin Lee
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Seung Soon Jang
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yongkuk Lee
- Department of Biomedical Engineering, Wichita State University, Wichita, Kansas 67260, United States
| | - Woon-Hong Yeo
- Wearable Intelligent Systems and Healthcare Center (WISH Center), Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Korea KIAT-Georgia Tech Semiconductor Electronics Center (K-GTSEC), Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, Georgia 30332, United States
- Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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Ali M, Hisham M, Abu Al-Rub RK, Butt H. Vat photopolymerization of multifunctional fresnel lenses for ocular management. Front Bioeng Biotechnol 2024; 12:1464129. [PMID: 39439550 PMCID: PMC11493721 DOI: 10.3389/fbioe.2024.1464129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2024] [Accepted: 09/24/2024] [Indexed: 10/25/2024] Open
Abstract
In this study, multifunctional Fresnel lenses were explored as a potential solution for correcting vision in patients with color vision deficiency (CVD) and high myopia. Current studies have primarily focused on color vision correction through the 3D printing of glasses and contact lenses. However, the potential of 3D-printed multifunctional devices, such as Fresnel lenses, goes beyond addressing a single vision correction issue. For this study, computer-aided design (CAD) model of Fresnel lens with high diopter based on constant height configuration was developed. The CAD model was successfully fabricated using vat photopolymerization 3D printer, employing laboratory-prepared transparent HEMA resin. The resin was modified with two Atto dyes (565 nm and 488 nm), known for their ability to filter out problematic wavelengths (400-500 nm and 540-580 nm) to address color vision deficiency. The printed lenses were characterized by their chemical, physical, and optical properties using various characterization techniques. The focusing performance was evaluated using focal length measurements, and the results obtained were less than 2 mm deviation from the design value, having the potential to assist in higher myopic vision correction. The resulting optical spectra were compared with commercial glasses, revealing close agreement for CVD correction. These results expand the potential applications of multifunctional Fresnel lenses in ophthalmology, demonstrating their effectiveness as vision-correcting lenses and imaging systems.
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Affiliation(s)
- Murad Ali
- Department of Mechanical and Nuclear Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Advanced Digital & Additive Manufacturing (ADAM) Center, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Muhammed Hisham
- Department of Mechanical and Nuclear Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Rashid K. Abu Al-Rub
- Department of Mechanical and Nuclear Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Advanced Digital & Additive Manufacturing (ADAM) Center, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Haider Butt
- Department of Mechanical and Nuclear Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
- Advanced Digital & Additive Manufacturing (ADAM) Center, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
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7
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Jang TM, Han WB, Han S, Dutta A, Lim JH, Kim T, Lim BH, Ko GJ, Shin JW, Kaveti R, Kang H, Eom CH, Choi SJ, Bandodkar AJ, Lee KS, Park E, Cheng H, Yeo WH, Hwang SW. Stretchable and biodegradable self-healing conductors for multifunctional electronics. SCIENCE ADVANCES 2024; 10:eadp9818. [PMID: 39231226 PMCID: PMC11373598 DOI: 10.1126/sciadv.adp9818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 07/29/2024] [Indexed: 09/06/2024]
Abstract
As the regenerative mechanisms of biological organisms, self-healing provides useful functions for soft electronics or associated systems. However, there have been few examples of soft electronics where all components have self-healing properties while also ensuring compatibility between components to achieve multifunctional and resilient bio-integrated electronics. Here, we introduce a stretchable, biodegradable, self-healing conductor constructed by combination of two layers: (i) synthetic self-healing elastomer and (ii) self-healing conductive composite with additives. Abundant dynamic disulfide and hydrogen bonds of the elastomer and conductive composite enable rapid and complete recovery of electrical conductivity (~1000 siemens per centimeter) and stretchability (~500%) in response to repetitive damages, and chemical interactions of interpenetrated polymer chains of these components facilitate robust adhesion strength, even under extreme mechanical stress. System-level demonstration of soft, self-healing electronics with diagnostic/therapeutic functions for the urinary bladder validates the possibility for versatile, practical uses in biomedical research areas.
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Affiliation(s)
- Tae-Min Jang
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Won Bae Han
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Seungkeun Han
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Ankan Dutta
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Center for Neural Engineering, The Pennsylvania State University, State College, University Park, PA 16802, USA
| | - Jun Hyeon Lim
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Taekyung Kim
- Biomedical Engineering Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea
- Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Bong Hee Lim
- Biomedical Engineering Research Center, Samsung Medical Center, Seoul 06351, Republic of Korea
- Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Gwan-Jin Ko
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Jeong-Woong Shin
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Rajaram Kaveti
- Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27606, USA
- Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST), North Carolina State University, Raleigh, NC 27606, USA
| | - Heeseok Kang
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Chan-Hwi Eom
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - So Jeong Choi
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
| | - Amay J Bandodkar
- Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27606, USA
- Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST), North Carolina State University, Raleigh, NC 27606, USA
| | - Kyu-Sung Lee
- Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea
- Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Eunkyoung Park
- Department of Biomedical Engineering, Soonchunhyang University, Asan 31538, Republic of Korea
| | - Huanyu Cheng
- Department of Engineering Science and Mechanics, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Materials Science and Engineering, The Pennsylvania State University, State College, University Park, PA 16802, USA
- Materials Research Institute, The Pennsylvania State University, State College, University Park, PA 16802, USA
| | - Woon-Hong Yeo
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- IEN Center for Wearable Intelligent Systems and Healthcare, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University School of Medicine, Atlanta, GA 30332, USA
- Parker H. Petit Institute for Bioengineering and Biosciences, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Suk-Won Hwang
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea
- Center for Biomaterials, Biomedical Research Institute, Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
- Department of Integrative Energy Engineering, Korea University, Seoul 02841, Republic of Korea
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Gao B, Jiang J, Zhou S, Li J, Zhou Q, Li X. Toward the Next Generation Human-Machine Interaction: Headworn Wearable Devices. Anal Chem 2024; 96:10477-10487. [PMID: 38888091 DOI: 10.1021/acs.analchem.4c01190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
Wearable devices are lightweight and portable devices worn directly on the body or integrated into the user's clothing or accessories. They are usually connected to the Internet and combined with various software applications to monitor the user's physical conditions. The latest research shows that wearable head devices, particularly those incorporating microfluidic technology, enable the monitoring of bodily fluids and physiological states. Here, we summarize the main forms, functions, and applications of head wearable devices through innovative researches in recent years. The main functions of wearable head devices are sensor monitoring, diagnosis, and even therapeutic interventions. Through this application, real-time monitoring of human physiological conditions and noninvasive treatment can be realized. Furthermore, microfluidics can realize real-time monitoring of body fluids and skin interstitial fluid, which is highly significant in medical diagnosis and has broad medical application prospects. However, despite the progress made, significant challenges persist in the integration of microfluidics into wearable devices at the current technological level. Herein, we focus on summarizing the cutting-edge applications of microfluidic contact lenses and offer insights into the burgeoning intersection between microfluidics and head-worn wearables, providing a glimpse into their future prospects.
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Affiliation(s)
- Bingbing Gao
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
| | - Jingwen Jiang
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
| | - Shu Zhou
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
| | - Jun Li
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
| | - Qian Zhou
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
| | - Xin Li
- School of Pharmaceutical Sciences, Nanjing Tech University, Nanjing 211816, P. R. China
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Lai H, Cai Q, Li M, Kong S, Wu Y, Yang H, Zhang Y, Ning H. Machine Learning-Guided Performance Evaluation of an All-Liquid Electrochromic Device. ACS APPLIED MATERIALS & INTERFACES 2024; 16:28798-28807. [PMID: 38775345 DOI: 10.1021/acsami.4c01277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
Electrochromic devices, capable of modulating light transmittance under the influence of an electric field, have garnered significant interest in the field of smart windows and car rearview mirrors. However, the development of high-performance electrochromic devices via large-scale explorations under miscellaneous experimental settings remains challenging and is still an urgent problem to be solved. In this study, we employed a two-step machine learning approach, combining machine learning algorithms such as KNN and XGBoost with the reality of electrochromic devices, to construct a comprehensive evaluation system for electrochromic materials. Utilizing our predictive evaluation system, we successfully screened the preparation conditions for the best-performing device, which was experimentally verified to have a high transmittance modulation amplitude (62.6%) and fast response time (5.7 s/7.1 s) at 70 A/m2. To test its stability, experiments over a long cycle time (1000 cycles) are performed. In this study, we develop an innovative framework for assessing the performance of electrochromic material devices. Our approach effectively filters experimental samples based on their distinct properties, substantially minimizing the expenditure of human and material resources in electrochromic research. Our approach to a mathematical machine learning evaluation framework for device performance has effectively propelled and informed research in electrochromic devices.
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Affiliation(s)
- Huayi Lai
- Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Foshan 528225, China
| | - Qingyue Cai
- Guangdong Basic Research Center of Excellence for Energy & Information Polymer Materials, State Key Laboratory of Luminescent Materials and Devices, School of Materials Science and Engineering, South China University of Technology, Guangzhou 510640, China
| | - MuYun Li
- Guangdong Basic Research Center of Excellence for Energy & Information Polymer Materials, State Key Laboratory of Luminescent Materials and Devices, School of Materials Science and Engineering, South China University of Technology, Guangzhou 510640, China
| | - Sifan Kong
- School of Software, South China Normal University, Foshan 528225, China
| | - Yitong Wu
- School of Electronics and Information Engineering, South China Normal University, Foshan 528225, China
| | - Huan Yang
- Aberdeen Institute of Data Science and Artificial Intelligence, South China Normal University, Foshan 528225, China
| | - Yong Zhang
- School of Semiconductor Science and Technology, South China Normal University, Foshan 528225, China
| | - Honglong Ning
- Guangdong Basic Research Center of Excellence for Energy & Information Polymer Materials, State Key Laboratory of Luminescent Materials and Devices, School of Materials Science and Engineering, South China University of Technology, Guangzhou 510640, China
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Zhuo S, Zhang A, Tessier A, Williams C, Kabiri Ameri S. Solvent-Free and Cost-Efficient Fabrication of a High-Performance Nanocomposite Sensor for Recording of Electrophysiological Signals. BIOSENSORS 2024; 14:188. [PMID: 38667181 PMCID: PMC11048393 DOI: 10.3390/bios14040188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 03/28/2024] [Accepted: 04/09/2024] [Indexed: 04/28/2024]
Abstract
Carbon nanotube (CNT)-based nanocomposites have found applications in making sensors for various types of physiological sensing. However, the sensors' fabrication process is usually complex, multistep, and requires longtime mixing and hazardous solvents that can be harmful to the environment. Here, we report a flexible dry silver (Ag)/CNT/polydimethylsiloxane (PDMS) nanocomposite-based sensor made by a solvent-free, low-temperature, time-effective, and simple approach for electrophysiological recording. By mechanical compression and thermal treatment of Ag/CNT, a connected conductive network of the fillers was formed, after which the PDMS was added as a polymer matrix. The CNTs make a continuous network for electrons transport, endowing the nanocomposite with high electrical conductivity, mechanical strength, and durability. This process is solvent-free and does not require a high temperature or complex mixing procedure. The sensor shows high flexibility and good conductivity. High-quality electroencephalography (EEG) and electrooculography (EOG) were performed using fabricated dry sensors. Our results show that the Ag/CNT/PDMS sensor has comparable skin-sensor interface impedance with commercial Ag/AgCl-coated dry electrodes, better performance for noninvasive electrophysiological signal recording, and a higher signal-to-noise ratio (SNR) even after 8 months of storage. The SNR of electrophysiological signal recording was measured to be 26.83 dB for our developed sensors versus 25.23 dB for commercial Ag/AgCl-coated dry electrodes. Our process of compress-heating the functional fillers provides a universal approach to fabricate various types of nanocomposites with different nanofillers and desired electrical and mechanical properties.
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Affiliation(s)
- Shuyun Zhuo
- Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Anan Zhang
- Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Alexandre Tessier
- Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Chris Williams
- Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Shideh Kabiri Ameri
- Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON K7L 3N6, Canada
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON K7L 3N6, Canada
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11
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Park J, Lee Y, Cho S, Choe A, Yeom J, Ro YG, Kim J, Kang DH, Lee S, Ko H. Soft Sensors and Actuators for Wearable Human-Machine Interfaces. Chem Rev 2024; 124:1464-1534. [PMID: 38314694 DOI: 10.1021/acs.chemrev.3c00356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Haptic human-machine interfaces (HHMIs) combine tactile sensation and haptic feedback to allow humans to interact closely with machines and robots, providing immersive experiences and convenient lifestyles. Significant progress has been made in developing wearable sensors that accurately detect physical and electrophysiological stimuli with improved softness, functionality, reliability, and selectivity. In addition, soft actuating systems have been developed to provide high-quality haptic feedback by precisely controlling force, displacement, frequency, and spatial resolution. In this Review, we discuss the latest technological advances of soft sensors and actuators for the demonstration of wearable HHMIs. We particularly focus on highlighting material and structural approaches that enable desired sensing and feedback properties necessary for effective wearable HHMIs. Furthermore, promising practical applications of current HHMI technology in various areas such as the metaverse, robotics, and user-interactive devices are discussed in detail. Finally, this Review further concludes by discussing the outlook for next-generation HHMI technology.
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Affiliation(s)
- Jonghwa Park
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Youngoh Lee
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Seungse Cho
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Ayoung Choe
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Jeonghee Yeom
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Yun Goo Ro
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Jinyoung Kim
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Dong-Hee Kang
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Seungjae Lee
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
| | - Hyunhyub Ko
- School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan Metropolitan City 44919, Republic of Korea
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12
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Liu T, Tang X, Zeng Y, Li Y, Jing C, Ling F, Yang H, Zhou X. C-Rich Carbon Nitride Conjugated Polymer Enabling Ion-Migration-Induced Precise Electrochromic Display. ACS APPLIED MATERIALS & INTERFACES 2023. [PMID: 38050907 DOI: 10.1021/acsami.3c15567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/07/2023]
Abstract
The development of electrochromic (EC) displays has been in the challenge of displaying precise patterns, such as characters or high-resolution images of small size. High-performance EC materials as well as efficient, precise-display strategies are still urgent. To enable a microfactor-guided strategy for highly precise display, I3-/I- ion-migration-induced localized electrochromism is developed in an EC device based on the C-rich polymeric carbon nitride (CPCN). The CPCN material with an extended conjugated backbone of individual aromatic nuclei and heptazine rings has been reported possessing remarkable photorechargeable performance. Owing to the self-charging behavior, the CPCN exhibits color switching by the interfacial charge recombination with I3- ions in electrolyte and serves as the EC material with a coloration efficiency of 210.2 cm2 C-1 and an optical contrast of 48.6%. Material synthesis, electrode preparation, device design and fabrication, mechanism analysis, and performance evaluation of the CPCN-based EC display device are described.
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Affiliation(s)
- Tingting Liu
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Xiao Tang
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yue Zeng
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yanhong Li
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Chuan Jing
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Faling Ling
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Hongmei Yang
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Xianju Zhou
- School of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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13
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Lee J, Park S, Lee J, Kim N, Kim MK. Recent advances of additively manufactured noninvasive kinematic biosensors. Front Bioeng Biotechnol 2023; 11:1303004. [PMID: 38047290 PMCID: PMC10690938 DOI: 10.3389/fbioe.2023.1303004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 10/31/2023] [Indexed: 12/05/2023] Open
Abstract
The necessity of reliable measurement data assessment in the realm of human life has experienced exponential growth due to its extensive utilization in health monitoring, rehabilitation, surgery, and long-term treatment. As a result, the significance of kinematic biosensors has substantially increased across various domains, including wearable devices, human-machine interaction, and bioengineering. Traditionally, the fabrication of skin-mounted biosensors involved complex and costly processes such as lithography and deposition, which required extensive preparation. However, the advent of additive manufacturing has revolutionized biosensor production by facilitating customized manufacturing, expedited processes, and streamlined fabrication. AM technology enables the development of highly sensitive biosensors capable of measuring a wide range of kinematic signals while maintaining a low-cost aspect. This paper provides a comprehensive overview of state-of-the-art noninvasive kinematic biosensors created using diverse AM technologies. The detailed development process and the specifics of different types of kinematic biosensors are also discussed. Unlike previous review articles that primarily focused on the applications of additively manufactured sensors based on their sensing data, this article adopts a unique approach by categorizing and describing their applications according to their sensing frequencies. Although AM technology has opened new possibilities for biosensor fabrication, the field still faces several challenges that need to be addressed. Consequently, this paper also outlines these challenges and provides an overview of future applications in the field. This review article offers researchers in academia and industry a comprehensive overview of the innovative opportunities presented by kinematic biosensors fabricated through additive manufacturing technologies.
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Affiliation(s)
- Jeonghoon Lee
- Department of Mechanical Convergence Engineering, Hanyang University, Seoul, Republic of Korea
| | - Sangmin Park
- Department of Mechanical Engineering, Gachon University, Seongnam, Republic of Korea
| | - Jaehoon Lee
- Department of Mechanical Engineering, Gachon University, Seongnam, Republic of Korea
| | - Namjung Kim
- Department of Mechanical Engineering, Gachon University, Seongnam, Republic of Korea
| | - Min Ku Kim
- School of Mechanical Engineering, Hanyang University, Seoul, Republic of Korea
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14
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Kim K, Yang H, Lee J, Lee WG. Metaverse Wearables for Immersive Digital Healthcare: A Review. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2303234. [PMID: 37740417 PMCID: PMC10625124 DOI: 10.1002/advs.202303234] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/15/2023] [Indexed: 09/24/2023]
Abstract
The recent exponential growth of metaverse technology has been instrumental in reshaping a myriad of sectors, not least digital healthcare. This comprehensive review critically examines the landscape and future applications of metaverse wearables toward immersive digital healthcare. The key technologies and advancements that have spearheaded the metamorphosis of metaverse wearables are categorized, encapsulating all-encompassed extended reality, such as virtual reality, augmented reality, mixed reality, and other haptic feedback systems. Moreover, the fundamentals of their deployment in assistive healthcare (especially for rehabilitation), medical and nursing education, and remote patient management and treatment are investigated. The potential benefits of integrating metaverse wearables into healthcare paradigms are multifold, encompassing improved patient prognosis, enhanced accessibility to high-quality care, and high standards of practitioner instruction. Nevertheless, these technologies are not without their inherent challenges and untapped opportunities, which span privacy protection, data safeguarding, and innovation in artificial intelligence. In summary, future research trajectories and potential advancements to circumvent these hurdles are also discussed, further augmenting the incorporation of metaverse wearables within healthcare infrastructures in the post-pandemic era.
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Affiliation(s)
- Kisoo Kim
- Intelligent Optical Module Research CenterKorea Photonics Technology Institute (KOPTI)Gwangju61007Republic of Korea
| | - Hyosill Yang
- Department of NursingCollege of Nursing ScienceKyung Hee UniversitySeoul02447Republic of Korea
| | - Jihun Lee
- Department of Mechanical EngineeringCollege of EngineeringKyung Hee UniversityYongin17104Republic of Korea
| | - Won Gu Lee
- Department of Mechanical EngineeringCollege of EngineeringKyung Hee UniversityYongin17104Republic of Korea
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15
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Nguyen A, Pogoncheff G, Dong BX, Bui N, Truong H, Pham N, Nguyen L, Nguyen-Huu H, Bui-Diem K, Vu-Tran-Thien Q, Duong-Quy S, Ha S, Vu T. A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation. Sci Rep 2023; 13:17515. [PMID: 37845236 PMCID: PMC10579321 DOI: 10.1038/s41598-023-43975-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 09/30/2023] [Indexed: 10/18/2023] Open
Abstract
Difficulty falling asleep is one of the typical insomnia symptoms. However, intervention therapies available nowadays, ranging from pharmaceutical to hi-tech tailored solutions, remain ineffective due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, and an ability to keep people asleep during the night. This paper aims to enhance the efficacy of such an intervention by proposing a novel sleep aid system that can sense multiple physiological signals continuously and simultaneously control auditory stimulation to evoke appropriate brain responses for fast sleep promotion. The system, a lightweight, comfortable, and user-friendly headband, employs a comprehensive set of algorithms and dedicated own-designed audio stimuli. Compared to the gold-standard device in 883 sleep studies on 377 subjects, the proposed system achieves (1) a strong correlation (0.89 ± 0.03) between the physiological signals acquired by ours and those from the gold-standard PSG, (2) an 87.8% agreement on automatic sleep scoring with the consensus scored by sleep technicians, and (3) a successful non-pharmacological real-time stimulation to shorten the duration of sleep falling by 24.1 min. Conclusively, our solution exceeds existing ones in promoting fast falling asleep, tracking sleep state accurately, and achieving high social acceptance through a reliable large-scale evaluation.
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Affiliation(s)
- Anh Nguyen
- Department of Computer Science, University of Montana, Missoula, MT, 59812, USA.
| | | | | | - Nam Bui
- Department of Electrical Engineering, University of Colorado Denver, Denver, CO, 80204, USA
| | - Hoang Truong
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Nhat Pham
- School of Computer Science and Informatics, Cardiff University, Cardiff, CF24 4AG, UK
| | | | - Hoang Nguyen-Huu
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Khue Bui-Diem
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Quan Vu-Tran-Thien
- University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
| | - Sy Duong-Quy
- Lam Dong Medical College, Da Lat City, Lam Dong Province, Vietnam
- Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam
- Hershey Medical Center, Penn State College of Medicine, Hershey, PA, 17033, USA
| | - Sangtae Ha
- Earable Inc., Boulder, CO, 80309, USA
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Tam Vu
- Earable Inc., Boulder, CO, 80309, USA
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, 80309, USA
- Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK
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16
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Clark KB. Communication consistency, completeness, and complexity of digital ideography in trustworthy mobile extended reality. Behav Brain Sci 2023; 46:e239. [PMID: 37779285 DOI: 10.1017/s0140525x23000791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Communication barriers long-associated with ideographs, including combinatorial grapholinguistic complexity, computational encoding-decoding complexity, and technological rendering and deployment, become trivialized through advancements in interoperable smart mobile digital devices. Such technologies impart unprecedented extended-reality user hazards only mitigated by unprecedented colloquial and bureaucratic societal norms. Digital age norms thus influence natural ideographic language origins and evolution in ways novel to human history.
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Affiliation(s)
- Kevin B Clark
- Cures Within Reach, Chicago, IL, USA www.linkedin.com/pub/kevin-clark/58/67/19a; https://access-ci.org
- Felidae Conservation Fund, Mill Valley, CA, USA
- Expert Network, Penn Center for Innovation, University of Pennsylvania, Philadelphia, PA, USA
- Network for Life Detection (NfoLD), NASA Astrobiology Program, NASA Ames Research Center, Mountain View, CA, USA
- Multi-Omics and Systems Biology & Artificial Intelligence and Machine Learning Analysis Working Groups, NASA GeneLab, NASA Ames Research Center, Mountain View, CA, USA
- Frontier Development Lab, NASA Ames Research Center, Mountain View, CA, USA
- SETI Institute, Mountain View, CA, USA
- Peace Innovation Institute, Stanford University, Palo Alto, CA, USA and The Hague, Netherlands
- Shared Interest Group for Natural and Artificial Intelligence (sigNAI), Max Planck Alumni Association, Berlin, Germany
- Biometrics and Nanotechnology Councils, Institute for Electrical and Electronics Engineers (IEEE), New York, NY, USA
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17
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RaviChandran N, Teo ZL, Ting DSW. Artificial intelligence enabled smart digital eye wearables. Curr Opin Ophthalmol 2023; 34:414-421. [PMID: 37527195 DOI: 10.1097/icu.0000000000000985] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
PURPOSE OF REVIEW Smart eyewear is a head-worn wearable device that is evolving as the next phase of ubiquitous wearables. Although their applications in healthcare are being explored, they have the potential to revolutionize teleophthalmology care. This review highlights their applications in ophthalmology care and discusses future scope. RECENT FINDINGS Smart eyewear equips advanced sensors, optical displays, and processing capabilities in a wearable form factor. Rapid technological developments and the integration of artificial intelligence are expanding their reach from consumer space to healthcare applications. This review systematically presents their applications in treating and managing eye-related conditions. This includes remote assessments, real-time monitoring, telehealth consultations, and the facilitation of personalized interventions. They also serve as low-vision assistive devices to help visually impaired, and can aid physicians with operational and surgical tasks. SUMMARY Wearables such as smart eyewear collects rich, continuous, objective, individual-specific data, which is difficult to obtain in a clinical setting. By leveraging sophisticated data processing and artificial intelligence based algorithms, these data can identify at-risk patients, recognize behavioral patterns, and make timely interventions. They promise cost-effective and personalized treatment for vision impairments in an effort to mitigate the global burden of eye-related conditions and aging.
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Affiliation(s)
| | - Zhen Ling Teo
- Singapore National Eye Center, Singapore Eye Research Institute
| | - Daniel S W Ting
- AI and Digital Innovations
- Singapore National Eye Center, Singapore Eye Research Institute
- Duke-NUS Medical School, National University Singapore, Singapore
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18
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Shi Y, Yang P, Lei R, Liu Z, Dong X, Tao X, Chu X, Wang ZL, Chen X. Eye tracking and eye expression decoding based on transparent, flexible and ultra-persistent electrostatic interface. Nat Commun 2023; 14:3315. [PMID: 37286541 DOI: 10.1038/s41467-023-39068-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 05/30/2023] [Indexed: 06/09/2023] Open
Abstract
Eye tracking provides valuable insight for analyzing visual attention and underlying thinking progress through the observation of eye movements. Here, a transparent, flexible and ultra-persistent electrostatic sensing interface is proposed for realizing active eye tracking (AET) system based on the electrostatic induction effect. Through a triple-layer structure combined with a dielectric bilayer and a rough-surface Ag nanowire (Ag NW) electrode layer, the inherent capacitance and interfacial trapping density of the electrostatic interface has been strongly enhanced, contributing to an unprecedented charge storage capability. The electrostatic charge density of the interface reached 1671.10 μC·m-2 with a charge-keeping rate of 96.91% after 1000 non-contact operation cycles, which can finally realize oculogyric detection with an angular resolution of 5°. Thus, the AET system enables real-time decoding eye movements for customer preference recording and eye-controlled human-computer interaction, supporting its limitless potentiality in commercial purpose, virtual reality, human computer interactions and medical monitoring.
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Affiliation(s)
- Yuxiang Shi
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Peng Yang
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Rui Lei
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
| | - Zhaoqi Liu
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Xuanyi Dong
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Xinglin Tao
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Xiangcheng Chu
- State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing, 100084, China
| | - Zhong Lin Wang
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China
- Georgia Institute of Technology, Atlanta, GA, 30332-0245, USA
| | - Xiangyu Chen
- CAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing, 100083, China.
- School of Nanoscience and Engineering, University of Chinese Academy of Sciences, 100049, Beijing, China.
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19
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Ban S, Lee YJ, Kwon S, Kim YS, Chang JW, Kim JH, Yeo WH. Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human-Machine Interfaces. ACS APPLIED ELECTRONIC MATERIALS 2023; 5:877-886. [PMID: 36873262 PMCID: PMC9979786 DOI: 10.1021/acsaelm.2c01436] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
Recent advances in wearable technologies have enabled ways for people to interact with external devices, known as human-machine interfaces (HMIs). Among them, electrooculography (EOG), measured by wearable devices, is used for eye movement-enabled HMI. Most prior studies have utilized conventional gel electrodes for EOG recording. However, the gel is problematic due to skin irritation, while separate bulky electronics cause motion artifacts. Here, we introduce a low-profile, headband-type, soft wearable electronic system with embedded stretchable electrodes, and a flexible wireless circuit to detect EOG signals for persistent HMIs. The headband with dry electrodes is printed with flexible thermoplastic polyurethane. Nanomembrane electrodes are prepared by thin-film deposition and laser cutting techniques. A set of signal processing data from dry electrodes demonstrate successful real-time classification of eye motions, including blink, up, down, left, and right. Our study shows that the convolutional neural network performs exceptionally well compared to other machine learning methods, showing 98.3% accuracy with six classes: the highest performance till date in EOG classification with only four electrodes. Collectively, the real-time demonstration of continuous wireless control of a two-wheeled radio-controlled car captures the potential of the bioelectronic system and the algorithm for targeting various HMI and virtual reality applications.
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Affiliation(s)
- Seunghyeb Ban
- School
of Engineering and Computer Science, Washington
State University, Vancouver, Washington 98686, United States
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yoon Jae Lee
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- School
of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Shinjae Kwon
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- George
W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yun-Soung Kim
- BioMedical
Engineering and Imaging Institute, Icahn
School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Jae Won Chang
- Department
of Otolaryngology Head and Neck Surgery, School of Medicine, Chungnam National University Hospital, Daejeon 35015, Republic of Korea
| | - Jong-Hoon Kim
- School
of Engineering and Computer Science, Washington
State University, Vancouver, Washington 98686, United States
- Department
of Mechanical Engineering, University of
Washington, Seattle, Washington 98195, United States
| | - Woon-Hong Yeo
- IEN
Center for Human-Centric Interfaces and Engineering at the Institute
for Electronics and Nanotechnology, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
- George
W. Woodruff School of Mechanical Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine, Atlanta, Georgia 30332, United States
- Parker
H. Petit Institute for Bioengineering and Biosciences, Institute for
Materials, Neural Engineering Center, Institute for Robotics and Intelligent
Machines, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
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20
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Kalasin S, Surareungchai W. Challenges of Emerging Wearable Sensors for Remote Monitoring toward Telemedicine Healthcare. Anal Chem 2023; 95:1773-1784. [PMID: 36629753 DOI: 10.1021/acs.analchem.2c02642] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Digitized telemedicine tools with the Internet of Things (IoT) started advancing into our daily lives and have been incorporated with commercial wearable gadgets for noninvasive remote health monitoring. The newly established tools have been steered toward a new era of decentralized healthcare. The advancement of a telemedicine wearable monitoring system has attracted enormous interest in the multimodal big data acquisition of real-time physiological and biochemical information via noninvasive methods for any health-related industries. The expectation of telemedicine wearable creation has been focused on early diagnosis of multiple diseases and minimizing the cost of high-tech and invasive treatments. However, only limited progress has been directed toward the development of telemedicine wearable sensors. This Perspective addresses the advancement of these wearable sensors that encounter multiple challenges on the forefront and technological gaps hampering the realization of health monitoring at molecular levels related to smart materials mostly limited to single use, issues of selectivity to analytes, low sensitivity to targets, miniaturization, and lack of artificial intelligence to perform multiple tasks and secure big data transfer. Sensor stability with minimized signal drift, on-body sensor reusability, and long-term continuous health monitoring provides key analytical challenges. This Perspective also focuses on, promotes, and highlights wearable sensors with a distinct capability to interconnect with telemedicine healthcare for physical sensing and multiplex sensing at deeper levels. Moreover, it points out some critical challenges in different material aspects and promotes what it will take to advance the current state-of-art wearable sensors for telemedicine healthcare. Ultimately, this Perspective is to draw attention to some potential blind spots of wearable technology development and to inspire further development of this integrated technology in mitigating multimorbidity in aging societies through health monitoring at molecular levels to identify signs of diseases.
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Affiliation(s)
- Surachate Kalasin
- Faculty of Science and Nanoscience & Nanotechnology Graduate Program, King Mongkut's University of Technology Thonburi, 10140 Bangkok, Thailand
| | - Werasak Surareungchai
- Pilot Plant Research and Development Laboratory, King Mongkut's University of Technology Thonburi, 10150 Bangkok, Thailand
- School of Bioresource and Technology, King Mongkut's University of Technology Thonburi, 10150 Bangkok, Thailand
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21
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On lightmyography based muscle-machine interfaces for the efficient decoding of human gestures and forces. Sci Rep 2023; 13:327. [PMID: 36609654 PMCID: PMC9822960 DOI: 10.1038/s41598-022-25982-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 12/07/2022] [Indexed: 01/09/2023] Open
Abstract
Conventional muscle-machine interfaces like Electromyography (EMG), have significant drawbacks, such as crosstalk, a non-linear relationship between the signal and the corresponding motion, and increased signal processing requirements. In this work, we introduce a new muscle-machine interfacing technique called lightmyography (LMG), that can be used to efficiently decode human hand gestures, motion, and forces from the detected contractions of the human muscles. LMG utilizes light propagation through elastic media and human tissue, measuring changes in light luminosity to detect muscle movement. Similar to forcemyography, LMG infers muscular contractions through tissue deformation and skin displacements. In this study, we look at how different characteristics of the light source and silicone medium affect the performance of LMG and we compare LMG and EMG based gesture decoding using various machine learning techniques. To do that, we design an armband equipped with five LMG modules, and we use it to collect the required LMG data. Three different machine learning methods are employed: Random Forests, Convolutional Neural Networks, and Temporal Multi-Channel Vision Transformers. The system has also been efficiently used in decoding the forces exerted during power grasping. The results demonstrate that LMG outperforms EMG for most methods and subjects.
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22
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Zarei M, Lee G, Lee SG, Cho K. Advances in Biodegradable Electronic Skin: Material Progress and Recent Applications in Sensing, Robotics, and Human-Machine Interfaces. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2203193. [PMID: 35737931 DOI: 10.1002/adma.202203193] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 06/13/2022] [Indexed: 06/15/2023]
Abstract
The rapid growth of the electronics industry and proliferation of electronic materials and telecommunications technologies has led to the release of a massive amount of untreated electronic waste (e-waste) into the environment. Consequently, catastrophic environmental damage at the microbiome level and serious human health diseases threaten the natural fate of the planet. Currently, the demand for wearable electronics for applications in personalized medicine, electronic skins (e-skins), and health monitoring is substantial and growing. Therefore, "green" characteristics such as biodegradability, self-healing, and biocompatibility ensure the future application of wearable electronics and e-skins in biomedical engineering and bioanalytical sciences. Leveraging the biodegradability, sustainability, and biocompatibility of natural materials will dramatically influence the fabrication of environmentally friendly e-skins and wearable electronics. Here, the molecular and structural characteristics of biological skins and artificial e-skins are discussed. The focus then turns to the biodegradable materials, including natural and synthetic-polymer-based materials, and their recent applications in the development of biodegradable e-skin in wearable sensors, robotics, and human-machine interfaces (HMIs). Finally, the main challenges and outlook regarding the preparation and application of biodegradable e-skins are critically discussed in a near-future scenario, which is expected to lead to the next generation of biodegradable e-skins.
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Affiliation(s)
- Mohammad Zarei
- Department of Chemistry, University of Ulsan, Ulsan, 44610, Korea
| | - Giwon Lee
- Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, 37673, Korea
| | - Seung Goo Lee
- Department of Chemistry, University of Ulsan, Ulsan, 44610, Korea
| | - Kilwon Cho
- Department of Chemical Engineering, Pohang University of Science and Technology, Pohang, 37673, Korea
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23
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Chen M, Ouyang J, Jian A, Liu J, Li P, Hao Y, Gong Y, Hu J, Zhou J, Wang R, Wang J, Hu L, Wang Y, Ouyang J, Zhang J, Hou C, Wei L, Zhou H, Zhang D, Tao G. Imperceptible, designable, and scalable braided electronic cord. Nat Commun 2022; 13:7097. [PMID: 36402785 PMCID: PMC9675780 DOI: 10.1038/s41467-022-34918-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 11/11/2022] [Indexed: 11/21/2022] Open
Abstract
Flexible sensors, friendly interfaces, and intelligent recognition are important in the research of novel human-computer interaction and the development of smart devices. However, major challenges are still encountered in designing user-centered smart devices with natural, convenient, and efficient interfaces. Inspired by the characteristics of textile-based flexible electronic sensors, in this article, we report a braided electronic cord with a low-cost, and automated fabrication to realize imperceptible, designable, and scalable user interfaces. The braided electronic cord is in a miniaturized form, which is suitable for being integrated with various occasions in life. To achieve high-precision interaction, a multi-feature fusion algorithm is designed to recognize gestures of different positions, different contact areas, and different movements performed on a single braided electronic cord. The recognized action results are fed back to varieties of interactive terminals, which show the diversity of cord forms and applications. Our braided electronic cord with the features of user friendliness, excellent durability and rich interaction mode will greatly promote the development of human-machine integration in the future.
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Affiliation(s)
- Min Chen
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jingyu Ouyang
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Aijia Jian
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jia Liu
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Pan Li
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Yixue Hao
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Yuchen Gong
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jiayu Hu
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jing Zhou
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Rui Wang
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jiaxi Wang
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Long Hu
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Yuwei Wang
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Ju Ouyang
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Jing Zhang
- grid.503241.10000 0004 1760 9015School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan), 430074 Wuhan, China
| | - Chong Hou
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China ,grid.33199.310000 0004 0368 7223School of Optical and Electronic Information, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Lei Wei
- grid.59025.3b0000 0001 2224 0361School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798 Singapore
| | - Huamin Zhou
- grid.33199.310000 0004 0368 7223State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China
| | - Dingyu Zhang
- grid.507952.c0000 0004 1764 577XWuhan Jinyintan Hospital, 430048 Wuhan, Hubei China ,Hubei Provincial Health and Health Committee, 430015 Wuhan, Hubei China
| | - Guangming Tao
- grid.33199.310000 0004 0368 7223Wuhan National Laboratory for Optoelectronics and School of Computer Science and Technology, Huazhong University of Science and Technology, 430074 Wuhan, China ,grid.33199.310000 0004 0368 7223State Key Laboratory of Material Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China
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24
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Ban S, Lee YJ, Kim KR, Kim JH, Yeo WH. Advances in Materials, Sensors, and Integrated Systems for Monitoring Eye Movements. BIOSENSORS 2022; 12:1039. [PMID: 36421157 PMCID: PMC9688058 DOI: 10.3390/bios12111039] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 11/11/2022] [Accepted: 11/13/2022] [Indexed: 06/16/2023]
Abstract
Eye movements show primary responses that reflect humans' voluntary intention and conscious selection. Because visual perception is one of the fundamental sensory interactions in the brain, eye movements contain critical information regarding physical/psychological health, perception, intention, and preference. With the advancement of wearable device technologies, the performance of monitoring eye tracking has been significantly improved. It also has led to myriad applications for assisting and augmenting human activities. Among them, electrooculograms, measured by skin-mounted electrodes, have been widely used to track eye motions accurately. In addition, eye trackers that detect reflected optical signals offer alternative ways without using wearable sensors. This paper outlines a systematic summary of the latest research on various materials, sensors, and integrated systems for monitoring eye movements and enabling human-machine interfaces. Specifically, we summarize recent developments in soft materials, biocompatible materials, manufacturing methods, sensor functions, systems' performances, and their applications in eye tracking. Finally, we discuss the remaining challenges and suggest research directions for future studies.
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Affiliation(s)
- Seunghyeb Ban
- School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yoon Jae Lee
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ka Ram Kim
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Jong-Hoon Kim
- School of Engineering and Computer Science, Washington State University, Vancouver, WA 98686, USA
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA
| | - Woon-Hong Yeo
- IEN Center for Human-Centric Interfaces and Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA 30332, USA
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University School of Medicine, Atlanta, GA 30332, USA
- Neural Engineering Center, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA
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25
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Cai Q, Yan H, Yao R, Luo D, Li M, Zhong J, Yang Y, Qiu T, Ning H, Peng J. From Traditional to Novel Printed Electrochromic Devices: Material, Structure and Device. MEMBRANES 2022; 12:1039. [PMID: 36363594 PMCID: PMC9695232 DOI: 10.3390/membranes12111039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 10/14/2022] [Accepted: 10/20/2022] [Indexed: 06/16/2023]
Abstract
Electrochromic materials have been considered as a new way to achieve energy savings in the building sector due to their potential applications in smart windows, cars, aircrafts, etc. However, the high cost of manufacturing ECDs using the conventional manufacturing methods has limited its commercialization. It is the advantages of low cost as well as resource saving, green environment protection, flexibility and large area production that make printing electronic technology fit for manufacturing electrochromic devices. This paper reviews the progress of research on printed electrochromic devices (ECDs), detailing the preparation of ECDs by screen printing, inkjet printing and 3D printing, using the scientific properties of discrete definition printing method. Up to now, screen printing holds the largest share in the electrochromic industry due to its low cost and large ink output nature, which makes it suitable especially for printing on large surfaces. Though inkjet printing has the advantages of high precision and the highest coloration efficiency (CE) can be up to 542 ± 10 cm2C-1, it has developed smoothly, and has not shown rigid needs. Inkjet printing is suitable for the personalized printing production of high precision and small batch electronic devices. Since 3D printing is a new manufacturing technology in the 21st century, with the characteristics of integrated molding and being highly controllable, which make it suitable for customized printing of complex devices, such as all kinds of sensors, it has gained increasing attention in the past decade. Finally, the possibility of combining screen printing with inkjet printing to produce high performance ECDs is discussed.
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Affiliation(s)
- Qingyue Cai
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Haoyang Yan
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Rihui Yao
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Dongxiang Luo
- School of Chemistry and Chemical Engineering, Institute of Clean Energy and Materials, Guangzhou Key Laboratory for Clean Energy and Materials, Huangpu Hydrogen Innovation Center, Guangzhou University, Guangzhou 510006, China
| | - Muyun Li
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Jinyao Zhong
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Yuexin Yang
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Tian Qiu
- Department of Intelligent Manufacturing, Wuyi University, Jiangmen 529020, China
| | - Honglong Ning
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
| | - Junbiao Peng
- State Key Laboratory of Luminescent Materials and Devices, Institute of Polymer Optoelectronic Materials and Devices, South China University of Technology, Guangzhou 510640, China
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26
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Abstract
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With the rapid development of optoelectronic fields,
electrochromic
(EC) materials and devices have received remarkable attention and
have shown attractive potential for use in emerging wearable and portable
electronics, electronic papers/billboards, see-through displays, and
other new-generation displays, due to the advantages of low power
consumption, easy viewing, flexibility, stretchability, etc. Despite
continuous progress in related fields, determining how to make electrochromics
truly meet the requirements of mature displays (e.g., ideal overall
performance) has been a long-term problem. Therefore, the commercialization
of relevant high-quality products is still in its infancy. In this
review, we will focus on the progress in emerging EC materials and
devices for potential displays, including two mainstream EC display
prototypes (segmented displays and pixel displays) and their commercial
applications. Among these topics, the related materials/devices, EC
performance, construction approaches, and processing techniques are
comprehensively disscussed and reviewed. We also outline the current
barriers with possible solutions and discuss the future of this field.
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Affiliation(s)
- Chang Gu
- State Key Lab of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, People's Republic of China
| | - Ai-Bo Jia
- State Key Lab of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, People's Republic of China
| | - Yu-Mo Zhang
- State Key Lab of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, People's Republic of China
| | - Sean Xiao-An Zhang
- State Key Lab of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012, People's Republic of China
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27
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Digital design and evaluation for additive manufacturing of personalized myopic glasses. Sci Rep 2022; 12:12926. [PMID: 35902626 PMCID: PMC9334356 DOI: 10.1038/s41598-022-17233-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 07/22/2022] [Indexed: 11/14/2022] Open
Abstract
Myopic glasses design has critical effects on the match between glasses and individual face. Improper myopic glasses design may affect the try-on comfort and health. It is difficult for the myopic glasses to be adjusted variedly and suitably from people to people with the limitations of traditional manufacturing processes and current design methods. In this paper, an evaluation descriptor named glasses fit score, which contains alignment scores and design scores, is proposed to guide and evaluate the myopic glasses design. Based on the descriptor, a novel approach is presented to complete the myopic glasses design and manufacturing individually. The approach can be divided into three steps: glasses alignment, glasses personalized design and glasses manufacturing. During the glasses alignment, the myopic glasses are aligned to the face to obtain the alignment score of the descriptor based on the face symmetry plane and feature points, including the silent point of the eye and the top point of the ear. After the glasses alignment, the myopic glasses can be deformed to match the face to achieve the design score of the descriptor. The deformations include glasses frame transformation, glasses leg option and glasses personalized mark. In the glasses manufacturing, the designed myopic glasses can be fabricated by a 3D printer. Then, a post processing process is conducted to polish the myopic glasses with oil painted. Finally, the proposed approach is applied to adjust the myopic glasses for several people. The results show that, compared to the previous methods, the approach can make the myopic glasses aligned and deformed to the individual face effectively to obtain an ideal score of the descriptor, thus improving the match between the glasses and the individual face.
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28
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Howard J, Murashov V, Cauda E, Snawder J. Advanced sensor technologies and the future of work. Am J Ind Med 2022; 65:3-11. [PMID: 34647336 DOI: 10.1002/ajim.23300] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 09/27/2021] [Accepted: 09/30/2021] [Indexed: 01/09/2023]
Abstract
Exposure science is fundamental to the field of occupational safety and health. The measurement of worker exposures to hazardous agents informs effective workplace risk mitigation strategies. The modern era of occupational exposure measurement began with the invention of the personal sampling device, which is still widely used today in the practice of occupational hygiene. Newer direct-reading sensor devices are incorporating recent advances in transducers, nanomaterials, electronics miniaturization, portability, batteries with high-power density, wireless communication, energy-efficient microprocessing, and display technology to usher in a new era in exposure science. Commercial applications of new sensor technologies have led to a variety of health and lifestyle management devices for everyday life. These applications are also being investigated as tools to measure occupational and environmental exposures. As the next-generation placeable, wearable, and implantable sensor technologies move from the research laboratory to the workplace, their role in the future of work will be of increasing importance to employers, workers, and occupational safety and health researchers and practitioners. This commentary discusses some of the benefits and challenges of placeable, wearable, and implantable sensor technologies in the future of work.
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Affiliation(s)
- John Howard
- Office of the Director, National Institute for Occupational Safety and Health, Washington District of Columbia USA
| | - Vladimir Murashov
- Office of the Director, National Institute for Occupational Safety and Health, Washington District of Columbia USA
| | - Emanuele Cauda
- Center for Direct Reading and Sensor Technologies, Pittsburgh Mining Research Division National Institute for Occupational Safety and Health Pittsburgh Pennsylvania USA
| | - John Snawder
- Center for Direct Reading and Sensor Technologies, Health Effects Laboratory Division National Institute for Occupational Safety and Health Cincinnati Ohio USA
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29
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Xiao Y, Wang M, Li Y, Sun Z, Liu Z, He L, Liu R. High-Adhesive Flexible Electrodes and Their Manufacture: A Review. MICROMACHINES 2021; 12:1505. [PMID: 34945355 PMCID: PMC8704330 DOI: 10.3390/mi12121505] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 11/02/2021] [Accepted: 11/08/2021] [Indexed: 12/21/2022]
Abstract
All human activity is associated with the generation of electrical signals. These signals are collectively referred to as electrical physiology (EP) signals (e.g., electrocardiogram, electroencephalogram, electromyography, electrooculography, etc.), which can be recorded by electrodes. EP electrodes are not only widely used in the study of primary diseases and clinical practice, but also have potential applications in wearable electronics, human-computer interface, and intelligent robots. Various technologies are required to achieve such goals. Among these technologies, adhesion and stretchable electrode technology is a key component for rapid development of high-performance sensors. In last decade, remarkable efforts have been made in the development of flexible and high-adhesive EP recording systems and preparation technologies. Regarding these advancements, this review outlines the design strategies and related materials for flexible and adhesive EP electrodes, and briefly summarizes their related manufacturing techniques.
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Affiliation(s)
- Yingying Xiao
- Beijing Engineering Research Center of Printed Electronics, Beijing Institute of Graphic Communication, Beijing 102600, China; (Y.X.); (M.W.); (Y.L.); (Z.S.)
| | - Mengzhu Wang
- Beijing Engineering Research Center of Printed Electronics, Beijing Institute of Graphic Communication, Beijing 102600, China; (Y.X.); (M.W.); (Y.L.); (Z.S.)
| | - Ye Li
- Beijing Engineering Research Center of Printed Electronics, Beijing Institute of Graphic Communication, Beijing 102600, China; (Y.X.); (M.W.); (Y.L.); (Z.S.)
| | - Zhicheng Sun
- Beijing Engineering Research Center of Printed Electronics, Beijing Institute of Graphic Communication, Beijing 102600, China; (Y.X.); (M.W.); (Y.L.); (Z.S.)
| | - Zilong Liu
- Division of Optics, National Institute of Metrology, Beijing 100029, China;
| | - Liang He
- School of Mechanical Engineering, Sichuan University, Chengdu 610065, China;
| | - Ruping Liu
- Beijing Engineering Research Center of Printed Electronics, Beijing Institute of Graphic Communication, Beijing 102600, China; (Y.X.); (M.W.); (Y.L.); (Z.S.)
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30
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Electropolymers of 4-(thieno[3,2-b]thiophen-3-yl)benzonitrile extended with thiophene, 3-hexylthiophene and EDOT moieties; their electrochromic applications. POLYMER 2021. [DOI: 10.1016/j.polymer.2021.124286] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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31
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The Relationship between Stress Levels Measured by a Questionnaire and the Data Obtained by Smart Glasses and Finger Pulse Oximeters among Polish Dental Students. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11188648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Stress is a physical, mental, or emotional response to a change and is a significant problem in modern society. In addition to questionnaires, levels of stress may be assessed by monitoring physiological signals, such as via photoplethysmogram (PPG), electroencephalogram (EEG), electrocardiogram (ECG), electrodermal activity (EDA), facial expressions, and head and body movements. In our study, we attempted to find the relationship between the perceived stress level and physiological signals, such as heart rate (HR), head movements, and electrooculographic (EOG) signals. The perceived stress level was acquired by self-assessment questionnaires in which the participants marked their stress level before, during, and after performing a task. The heart rate was acquired with a finger pulse oximeter and the head movements (linear acceleration and angular velocity) and electrooculographic signals were recorded with JINS MEME ES_R smart glasses (JINS Holdings, Inc., Tokyo, Japan). We observed significant differences between the perceived stress level, heart rate, the power of linear acceleration, angular velocity, and EOG signals before performing the task and during the task. However, except for HR, these signals were poorly correlated with the perceived stress level acquired during the task.
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32
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Abstract
Smart materials are a kind of functional materials which can sense and response to environmental conditions or stimuli from optical, electrical, magnetic mechanical, thermal, and chemical signals, etc. Patterning of smart materials is the key to achieving large-scale arrays of functional devices. Over the last decades, printing methods including inkjet printing, template-assisted printing, and 3D printing are extensively investigated and utilized in fabricating intelligent micro/nano devices, as printing strategies allow for constructing multidimensional and multimaterial architectures. Great strides in printable smart materials are opening new possibilities for functional devices to better serve human beings, such as wearable sensors, integrated optoelectronics, artificial neurons, and so on. However, there are still many challenges and drawbacks that need to be overcome in order to achieve the controllable modulation between smart materials and device performance. In this review, we give an overview on printable smart materials, printing strategies, and applications of printed functional devices. In addition, the advantages in actual practices of printing smart materials-based devices are discussed, and the current limitations and future opportunities are proposed. This review aims to summarize the recent progress and provide reference for novel smart materials and printing strategies as well as applications of intelligent devices.
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Affiliation(s)
- Meng Su
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS), Zhongguancun North First Street 2, 100190 Beijing, P. R. China.,University of Chinese Academy of Sciences, Yuquan Road no.19A, 100049 Beijing, P. R. China
| | - Yanlin Song
- Key Laboratory of Green Printing, Institute of Chemistry, Chinese Academy of Sciences, Beijing Engineering Research Center of Nanomaterials for Green Printing Technology, Beijing National Laboratory for Molecular Sciences (BNLMS), Zhongguancun North First Street 2, 100190 Beijing, P. R. China.,University of Chinese Academy of Sciences, Yuquan Road no.19A, 100049 Beijing, P. R. China
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33
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Zhou H, Li D, He X, Hui X, Guo H, Hu C, Mu X, Wang ZL. Bionic Ultra-Sensitive Self-Powered Electromechanical Sensor for Muscle-Triggered Communication Application. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2101020. [PMID: 34081406 PMCID: PMC8336610 DOI: 10.1002/advs.202101020] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 04/15/2021] [Indexed: 06/12/2023]
Abstract
The past few decades have witnessed the tremendous progress of human-machine interface (HMI) in communication, education, and manufacturing fields. However, due to signal acquisition devices' limitations, the research on HMI related to communication aid applications for the disabled is progressing slowly. Here, inspired by frogs' croaking behavior, a bionic triboelectric nanogenerator (TENG)-based ultra-sensitive self-powered electromechanical sensor for muscle-triggered communication HMI application is developed. The sensor possesses a high sensitivity (54.6 mV mm-1 ), a high-intensity signal (± 700 mV), and a wide sensing range (0-5 mm). The signal intensity is 206 times higher than that of traditional biopotential electromyography methods. By leveraging machine learning algorithms and Morse code, the safe, accurate (96.3%), and stable communication aid HMI applications are achieved. The authors' bionic TENG-based electromechanical sensor provides a valuable toolkit for HMI applications of the disabled, and it brings new insights into the interdisciplinary cross-integration between TENG technology and bionics.
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Affiliation(s)
- Hong Zhou
- Key Laboratory of Optoelectronic Technology & SystemsMinistry of Educationand International R & D center of Micro‐nano Systems and New Materials TechnologyChongqing UniversityChongqing400044P. R. China
| | - Dongxiao Li
- Key Laboratory of Optoelectronic Technology & SystemsMinistry of Educationand International R & D center of Micro‐nano Systems and New Materials TechnologyChongqing UniversityChongqing400044P. R. China
| | - Xianming He
- Key Laboratory of Optoelectronic Technology & SystemsMinistry of Educationand International R & D center of Micro‐nano Systems and New Materials TechnologyChongqing UniversityChongqing400044P. R. China
| | - Xindan Hui
- Key Laboratory of Optoelectronic Technology & SystemsMinistry of Educationand International R & D center of Micro‐nano Systems and New Materials TechnologyChongqing UniversityChongqing400044P. R. China
| | - Hengyu Guo
- Department of Applied PhysicsChongqing UniversityChongqing400044P. R. China
| | - Chenguo Hu
- Department of Applied PhysicsChongqing UniversityChongqing400044P. R. China
| | - Xiaojing Mu
- Key Laboratory of Optoelectronic Technology & SystemsMinistry of Educationand International R & D center of Micro‐nano Systems and New Materials TechnologyChongqing UniversityChongqing400044P. R. China
| | - Zhong Lin Wang
- Beijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing100083P. R. China
- School of Material Science and EngineeringGeorgia Institute of TechnologyAtlantaGA30332‐0245USA
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Schindler KA, Rahimi A. A Primer on Hyperdimensional Computing for iEEG Seizure Detection. Front Neurol 2021; 12:701791. [PMID: 34354666 PMCID: PMC8329339 DOI: 10.3389/fneur.2021.701791] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 06/18/2021] [Indexed: 11/13/2022] Open
Abstract
A central challenge in today's care of epilepsy patients is that the disease dynamics are severely under-sampled in the currently typical setting with appointment-based clinical and electroencephalographic examinations. Implantable devices to monitor electrical brain signals and to detect epileptic seizures may significantly improve this situation and may inform personalized treatment on an unprecedented scale. These implantable devices should be optimized for energy efficiency and compact design. Energy efficiency will ease their maintenance by reducing the time of recharging, or by increasing the lifetime of their batteries. Biological nervous systems use an extremely small amount of energy for information processing. In recent years, a number of methods, often collectively referred to as brain-inspired computing, have also been developed to improve computation in non-biological hardware. Here, we give an overview of one of these methods, which has in particular been inspired by the very size of brains' circuits and termed hyperdimensional computing. Using a tutorial style, we set out to explain the key concepts of hyperdimensional computing including very high-dimensional binary vectors, the operations used to combine and manipulate these vectors, and the crucial characteristics of the mathematical space they inhabit. We then demonstrate step-by-step how hyperdimensional computing can be used to detect epileptic seizures from intracranial electroencephalogram (EEG) recordings with high energy efficiency, high specificity, and high sensitivity. We conclude by describing potential future clinical applications of hyperdimensional computing for the analysis of EEG and non-EEG digital biomarkers.
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Affiliation(s)
- Kaspar A Schindler
- Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, NeuroTec, Bern University Hospital, University Bern, Bern, Switzerland
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Gong Z. Layer-Scale and Chip-Scale Transfer Techniques for Functional Devices and Systems: A Review. NANOMATERIALS (BASEL, SWITZERLAND) 2021; 11:842. [PMID: 33806237 PMCID: PMC8065746 DOI: 10.3390/nano11040842] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 03/16/2021] [Accepted: 03/22/2021] [Indexed: 02/07/2023]
Abstract
Hetero-integration of functional semiconductor layers and devices has received strong research interest from both academia and industry. While conventional techniques such as pick-and-place and wafer bonding can partially address this challenge, a variety of new layer transfer and chip-scale transfer technologies have been developed. In this review, we summarize such transfer techniques for heterogeneous integration of ultrathin semiconductor layers or chips to a receiving substrate for many applications, such as microdisplays and flexible electronics. We showed that a wide range of materials, devices, and systems with expanded functionalities and improved performance can be demonstrated by using these technologies. Finally, we give a detailed analysis of the advantages and disadvantages of these techniques, and discuss the future research directions of layer transfer and chip transfer techniques.
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Affiliation(s)
- Zheng Gong
- Institute of Semiconductors, Guangdong Academy of Sciences, No. 363 Changxing Road, Tianhe District, Guangzhou 510650, China;
- Foshan Debao Display Technology Co Ltd., Room 508-1, Level 5, Block A, Golden Valley Optoelectronics, Nanhai District, Foshan 528200, China
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