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Bhatia A, Hanna J, Stuart T, Kasper KA, Clausen DM, Gutruf P. Wireless Battery-free and Fully Implantable Organ Interfaces. Chem Rev 2024; 124:2205-2280. [PMID: 38382030 DOI: 10.1021/acs.chemrev.3c00425] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/23/2024]
Abstract
Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-free power supplies are resulting in a new generation of fully implantable organ interfaces that leverage volumetric reduction and soft mechanics by eliminating electrochemical power storage. This device class offers the ability to provide high-fidelity readouts of physiological processes, enables stimulation, and allows control over organs to realize new therapeutic and diagnostic paradigms. Driven by seamless integration with connected infrastructure, these devices enable personalized digital medicine. Key to advances are carefully designed material, electrophysical, electrochemical, and electromagnetic systems that form implantables with mechanical properties closely matched to the target organ to deliver functionality that supports high-fidelity sensors and stimulators. The elimination of electrochemical power supplies enables control over device operation, anywhere from acute, to lifetimes matching the target subject with physical dimensions that supports imperceptible operation. This review provides a comprehensive overview of the basic building blocks of battery-free organ interfaces and related topics such as implantation, delivery, sterilization, and user acceptance. State of the art examples categorized by organ system and an outlook of interconnection and advanced strategies for computation leveraging the consistent power influx to elevate functionality of this device class over current battery-powered strategies is highlighted.
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Affiliation(s)
- Aman Bhatia
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Jessica Hanna
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Tucker Stuart
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Kevin Albert Kasper
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - David Marshall Clausen
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
| | - Philipp Gutruf
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Department of Electrical and Computer Engineering, The University of Arizona, Tucson, Arizona 85721, United States
- Bio5 Institute, The University of Arizona, Tucson, Arizona 85721, United States
- Neuroscience Graduate Interdisciplinary Program (GIDP), The University of Arizona, Tucson, Arizona 85721, United States
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Devi DH, Duraisamy K, Armghan A, Alsharari M, Aliqab K, Sorathiya V, Das S, Rashid N. 5G Technology in Healthcare and Wearable Devices: A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23052519. [PMID: 36904721 PMCID: PMC10007389 DOI: 10.3390/s23052519] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 06/12/2023]
Abstract
Wearable devices with 5G technology are currently more ingrained in our daily lives, and they will now be a part of our bodies too. The requirement for personal health monitoring and preventive disease is increasing due to the predictable dramatic increase in the number of aging people. Technologies with 5G in wearables and healthcare can intensely reduce the cost of diagnosing and preventing diseases and saving patient lives. This paper reviewed the benefits of 5G technologies, which are implemented in healthcare and wearable devices such as patient health monitoring using 5G, continuous monitoring of chronic diseases using 5G, management of preventing infectious diseases using 5G, robotic surgery using 5G, and 5G with future of wearables. It has the potential to have a direct effect on clinical decision making. This technology could improve patient rehabilitation outside of hospitals and monitor human physical activity continuously. This paper draws the conclusion that the widespread adoption of 5G technology by healthcare systems enables sick people to access specialists who would be unavailable and receive correct care more conveniently.
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Affiliation(s)
- Delshi Howsalya Devi
- Department of AI & DS, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu 603308, Tamil Nadu, India
| | - Kumutha Duraisamy
- Department of Biomedical Engineering, Karpaga Vinayaga College of Engineering and Technology, Chengalpattu 603308, Tamil Nadu, India
| | - Ammar Armghan
- Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
| | - Meshari Alsharari
- Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
| | - Khaled Aliqab
- Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
| | - Vishal Sorathiya
- Faculty of Engineering and Technology, Parul Institute of Engineering and Technology, Parul University, Waghodia Road, Vadodara 391760, Gujarat, India
| | - Sudipta Das
- Department of Electronics and Communication Engineering, IMPS College of Engineering and Technology, Malda 732103, West Bengal, India
| | - Nasr Rashid
- Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka 72388, Saudi Arabia
- Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Nasr City, Cairo 11884, Egypt
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5
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Deiana AM, Tran N, Agar J, Blott M, Di Guglielmo G, Duarte J, Harris P, Hauck S, Liu M, Neubauer MS, Ngadiuba J, Ogrenci-Memik S, Pierini M, Aarrestad T, Bähr S, Becker J, Berthold AS, Bonventre RJ, Müller Bravo TE, Diefenthaler M, Dong Z, Fritzsche N, Gholami A, Govorkova E, Guo D, Hazelwood KJ, Herwig C, Khan B, Kim S, Klijnsma T, Liu Y, Lo KH, Nguyen T, Pezzullo G, Rasoulinezhad S, Rivera RA, Scholberg K, Selig J, Sen S, Strukov D, Tang W, Thais S, Unger KL, Vilalta R, von Krosigk B, Wang S, Warburton TK. Applications and Techniques for Fast Machine Learning in Science. Front Big Data 2022; 5:787421. [PMID: 35496379 PMCID: PMC9041419 DOI: 10.3389/fdata.2022.787421] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/31/2020] [Indexed: 01/10/2023] Open
Abstract
In this community review report, we discuss applications and techniques for fast machine learning (ML) in science-the concept of integrating powerful ML methods into the real-time experimental data processing loop to accelerate scientific discovery. The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for training and implementing performant and resource-efficient ML algorithms; and computing architectures, platforms, and technologies for deploying these algorithms. We also present overlapping challenges across the multiple scientific domains where common solutions can be found. This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions. This is followed by a high-level overview and organization of technical advances, including an abundance of pointers to source material, which can enable these breakthroughs.
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Affiliation(s)
| | - Nhan Tran
- Fermi National Accelerator Laboratory, Batavia, IL, United States
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Joshua Agar
- Department of Materials Science and Engineering, Lehigh University, Bethlehem, PA, United States
| | | | | | - Javier Duarte
- Department of Physics, University of California, San Diego, San Diego, CA, United States
| | - Philip Harris
- Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Scott Hauck
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, United States
| | - Mia Liu
- Department of Physics and Astronomy, Purdue University, West Lafayette, IN, United States
| | - Mark S. Neubauer
- Department of Physics, University of Illinois Urbana-Champaign, Champaign, IL, United States
| | | | - Seda Ogrenci-Memik
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | - Maurizio Pierini
- European Organization for Nuclear Research (CERN), Meyrin, Switzerland
| | - Thea Aarrestad
- European Organization for Nuclear Research (CERN), Meyrin, Switzerland
| | - Steffen Bähr
- Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Jürgen Becker
- Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Anne-Sophie Berthold
- Institute of Nuclear and Particle Physics, Technische Universität Dresden, Dresden, Germany
| | | | - Tomás E. Müller Bravo
- Department of Physics and Astronomy, University of Southampton, Southampton, United Kingdom
| | - Markus Diefenthaler
- Thomas Jefferson National Accelerator Facility, Newport News, VA, United States
| | - Zhen Dong
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States
| | - Nick Fritzsche
- Institute of Nuclear and Particle Physics, Technische Universität Dresden, Dresden, Germany
| | - Amir Gholami
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States
| | | | - Dongning Guo
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States
| | | | - Christian Herwig
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - Babar Khan
- Department of Computer Science, Technical University Darmstadt, Darmstadt, Germany
| | - Sehoon Kim
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States
| | - Thomas Klijnsma
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - Yaling Liu
- Department of Bioengineering, Lehigh University, Bethlehem, PA, United States
| | - Kin Ho Lo
- Department of Physics, University of Florida, Gainesville, FL, United States
| | - Tri Nguyen
- Massachusetts Institute of Technology, Cambridge, MA, United States
| | | | | | - Ryan A. Rivera
- Fermi National Accelerator Laboratory, Batavia, IL, United States
| | - Kate Scholberg
- Department of Physics, Duke University, Durham, NC, United States
| | | | - Sougata Sen
- Birla Institute of Technology and Science, Pilani, India
| | - Dmitri Strukov
- Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - William Tang
- Department of Physics, Princeton University, Princeton, NJ, United States
| | - Savannah Thais
- Department of Physics, Princeton University, Princeton, NJ, United States
| | | | - Ricardo Vilalta
- Department of Computer Science, University of Houston, Houston, TX, United States
| | - Belina von Krosigk
- Karlsruhe Institute of Technology, Karlsruhe, Germany
- Department of Physics, Universität Hamburg, Hamburg, Germany
| | - Shen Wang
- Department of Physics, University of Florida, Gainesville, FL, United States
| | - Thomas K. Warburton
- Department of Physics and Astronomy, Iowa State University, Ames, IA, United States
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Barrios-Ulloa A, Cama-Pinto D, Mardini-Bovea J, Díaz-Martínez J, Cama-Pinto A. Projections of IoT Applications in Colombia Using 5G Wireless Networks. SENSORS (BASEL, SWITZERLAND) 2021; 21:7167. [PMID: 34770472 PMCID: PMC8587546 DOI: 10.3390/s21217167] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 10/18/2021] [Accepted: 10/25/2021] [Indexed: 11/16/2022]
Abstract
Wireless technologies are increasingly relevant in different activities and lines of the economy, as well as in the daily life of people and companies. The advent of fifth generation networks (5G) implies a promising synergy with the Internet of Things (IoT), allowing for more automations in production processes and an increase in the efficiency of information transmission, managing to improve the efficiency in decision-making through tools such as big data and artificial intelligence. This article presents a description of the 5G implementation process in Colombia, as well as a revision of opportunities when combining with IoT in featured sectors of the departmental development plans, such as agriculture, tourism, health, the environment, and industry. Results shows that the startup of 5G in Colombia has been a slow process, but there are comparisons with similar procedures in other developed countries. Additionally, we present examples of 5G and IoT applications which can be promoted in Colombia, aimed at improving the quality of life of their habitants and promoting economic development.
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Affiliation(s)
- Alexis Barrios-Ulloa
- Department of Electronics Engineering, Faculty of Engineering, Universidad de Sucre, Sincelejo 700001, Colombia; or
- Department of Computer Science and Electronics, Universidad de la Costa, Bicentennial Scolarship–Ministry of Sciences, Barranquilla 080002, Colombia;
| | - Dora Cama-Pinto
- Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain
| | - Johan Mardini-Bovea
- Faculty of Engineering, Universidad del Atlántico, Barranquilla 081001, Colombia;
| | - Jorge Díaz-Martínez
- Department of Computer Science and Electronics, Universidad de la Costa, Bicentennial Scolarship–Ministry of Sciences, Barranquilla 080002, Colombia;
| | - Alejandro Cama-Pinto
- Department of Computer Science and Electronics, Universidad de la Costa, Barranquilla 080002, Colombia
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