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Chen L, Hu K, Lu M, Chen Z, Chen X, Zhou T, Liu X, Yin W, Casiraghi C, Song X. Wearable Sensors for Breath Monitoring Based on Water-Based Hexagonal Boron Nitride Inks Made with Supramolecular Functionalization. Adv Mater 2024; 36:e2312621. [PMID: 38168037 DOI: 10.1002/adma.202312621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Indexed: 01/05/2024]
Abstract
Wearable humidity sensors are attracting strong attention as they allow for real-time and continuous monitoring of important physiological information by enabling activity tracking as well as air quality assessment. Amongst 2Dimensional (2D) materials, graphene oxide (GO) is very attractive for humidity sensing due to its tuneable surface chemistry, high surface area, processability in water, and easy integration onto flexible substrates. However, strong hysteresis, low sensitivity, and cross-sensitivity issues limit the use of GO in practical applications, where continuous monitoring is preferred. Herein, a wearable and wireless impedance-based humidity sensor made with pyrene-functionalized hexagonal boron nitride (h-BN) nanosheets is demonstrated. The device shows enhanced sensitivity towards relative humidity (RH) (>1010 Ohms/%RH in the range from 5% to 100% RH), fast response (0.1 ms), no appreciable hysteresis, and no cross-sensitivity with temperature in the range of 25-60 °C. The h-BN-based sensor is able to monitor the whole breathing cycle process of exhaling and inhaling, hence enabling to record in real-time the subtlest changes of respiratory signals associated with different daily activities as well as various symptoms of flu, without requiring any direct contact with the individual.
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Affiliation(s)
- Liming Chen
- Department of Chemistry, University of Manchester, Manchester, M13 9PL, UK
- Department of Electrical and Electronic Engineering, University of Manchester, Manchester, M13 9PL, UK
| | - Kui Hu
- Department of Chemistry, University of Manchester, Manchester, M13 9PL, UK
| | - Mingyang Lu
- Department of Electrical and Electronic Engineering, University of Manchester, Manchester, M13 9PL, UK
| | - Ziqi Chen
- Department of Electrical and Electronic Engineering, University of Manchester, Manchester, M13 9PL, UK
| | - Xiwen Chen
- College of Energy, Soochow Institute for Energy and Materials InnovationS (SIEMIS), Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy Technologies, Soochow University, Suzhou, 215006, P. R. China
| | - Tianqi Zhou
- Department of Electrical and Electronic Engineering, University of Manchester, Manchester, M13 9PL, UK
| | - Xuqing Liu
- Department of Materials Science, University of Manchester, Manchester, M13 9PL, UK
| | - Wuliang Yin
- Department of Electrical and Electronic Engineering, University of Manchester, Manchester, M13 9PL, UK
| | - Cinzia Casiraghi
- Department of Chemistry, University of Manchester, Manchester, M13 9PL, UK
| | - Xiuju Song
- Department of Chemistry, University of Manchester, Manchester, M13 9PL, UK
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2
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Skoric J, D’Mello Y, Plant DV. A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography. IEEE J Transl Eng Health Med 2024; 12:348-358. [PMID: 38606390 PMCID: PMC11008810 DOI: 10.1109/jtehm.2024.3368291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/09/2024] [Accepted: 02/19/2024] [Indexed: 04/13/2024]
Abstract
Wearable sensing has become a vital approach to cardiac health monitoring, and seismocardiography (SCG) is emerging as a promising technology in this field. However, the applicability of SCG is hindered by motion artifacts, including those encountered in practice of which the strongest source is walking. This holds back the translation of SCG to clinical settings. We therefore investigated techniques to enhance the quality of SCG signals in the presence of motion artifacts. To simulate ambulant recordings, we corrupted a clean SCG dataset with real-walking-vibrational noise. We decomposed the signal using several empirical-mode-decomposition methods and the maximum overlap discrete wavelet transform (MODWT). By combining MODWT, time-frequency masking, and nonnegative matrix factorization, we developed a novel algorithm which leveraged the vertical axis accelerometer to reduce walking vibrations in dorsoventral SCG. The accuracy and applicability of our method was verified using heart rate estimation. We used an interactive selection approach to improve estimation accuracy. The best decomposition method for reduction of motion artifact noise was the MODWT. Our algorithm improved heart rate estimation from 0.1 to 0.8 r-squared at -15 dB signal-to-noise ratio (SNR). Our method reduces motion artifacts in SCG signals up to a SNR of -19 dB without requiring any external assistance from electrocardiography (ECG). Such a standalone solution is directly applicable to the usage of SCG in daily life, as a content-rich replacement for other wearables in clinical settings, and other continuous monitoring scenarios. In applications with higher noise levels, ECG may be incorporated to further enhance SCG and extend its usable range. This work addresses the challenges posed by motion artifacts, enabling SCG to offer reliable cardiovascular insights in more difficult scenarios, and thereby facilitating wearable monitoring in daily life and the clinic.
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Affiliation(s)
- James Skoric
- Department of Electrical and Computer EngineeringMcGill UniversityMontrealQCH3A 0E9Canada
| | - Yannick D’Mello
- Department of Electrical and Computer EngineeringMcGill UniversityMontrealQCH3A 0E9Canada
| | - David V. Plant
- Department of Electrical and Computer EngineeringMcGill UniversityMontrealQCH3A 0E9Canada
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3
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Hafid A, Gunnarsson E, Ramos A, Rödby K, Abtahi F, Bamidis PD, Billis A, Papachristou P, Seoane F. Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities. Sensors (Basel) 2023; 23:9208. [PMID: 38005593 PMCID: PMC10675781 DOI: 10.3390/s23229208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/09/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023]
Abstract
The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.
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Affiliation(s)
- Abdelakram Hafid
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business Swedish School of Textiles, University of Borås, 503 32 Borås, Sweden; (E.G.); (A.R.); (K.R.); (F.S.)
- School of Innovation, Design and Engineering, Mälardalen University, 722 20 Västerås, Sweden
| | - Emanuel Gunnarsson
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business Swedish School of Textiles, University of Borås, 503 32 Borås, Sweden; (E.G.); (A.R.); (K.R.); (F.S.)
| | - Alberto Ramos
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business Swedish School of Textiles, University of Borås, 503 32 Borås, Sweden; (E.G.); (A.R.); (K.R.); (F.S.)
- UDIT—University of Design, Innovation and Technology, 28016 Madrid, Spain
| | - Kristian Rödby
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business Swedish School of Textiles, University of Borås, 503 32 Borås, Sweden; (E.G.); (A.R.); (K.R.); (F.S.)
| | - Farhad Abtahi
- Institute for Clinical Science, Intervention and Technology, Karolinska Institutet, 141 83 Stockholm, Sweden;
- Department of Medical Care Technology, Karolinska University Hospital, 141 57 Huddinge, Sweden
- Department of Clinical Physiology, Karolinska University Hospital, 141 57 Huddinge, Sweden
| | - Panagiotis D. Bamidis
- Lab of Medical Physics and Digital Innovation, School of Medicine, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (P.D.B.); (A.B.)
| | - Antonis Billis
- Lab of Medical Physics and Digital Innovation, School of Medicine, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece; (P.D.B.); (A.B.)
| | - Panagiotis Papachristou
- Academic Primary Health Care Center, Region Stockholm, 104 31 Stockholm, Sweden;
- Division of Family Medicine and Primary Care, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 141 83 Stockholm, Sweden
| | - Fernando Seoane
- Textile Materials Technology, Department of Textile Technology, Faculty of Textiles, Engineering and Business Swedish School of Textiles, University of Borås, 503 32 Borås, Sweden; (E.G.); (A.R.); (K.R.); (F.S.)
- Institute for Clinical Science, Intervention and Technology, Karolinska Institutet, 141 83 Stockholm, Sweden;
- Department of Medical Care Technology, Karolinska University Hospital, 141 57 Huddinge, Sweden
- Department of Clinical Physiology, Karolinska University Hospital, 141 57 Huddinge, Sweden
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Eisenkraft A, Goldstein N, Fons M, Tabi M, Sherman AD, Ben Ishay A, Merin R, Nachman D. Comparing body temperature measurements using the double sensor method within a wearable device with oral and core body temperature measurements using medical grade thermometers-a short report. Front Physiol 2023; 14:1279314. [PMID: 38033330 PMCID: PMC10685445 DOI: 10.3389/fphys.2023.1279314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/02/2023] [Indexed: 12/02/2023] Open
Abstract
Introduction: Body temperature is essential for diagnosing, managing, and following multiple medical conditions. There are several methods and devices to measure body temperature, but most do not allow continuous and prolonged measurement of body temperature. Noninvasive skin temperature sensor combined with a heat flux sensor, also known as the "double sensor" technique, is becoming a valuable and simple method for frequently monitoring body temperature. Methods: Body temperature measurements using the "double sensor" method in a wearable monitoring device were compared with oral and core body temperature measurements using medical grade thermometers, analyzing data from two prospective clinical trials of different clinical scenarios. One study included 45 hospitalized COVID-19 patients in which oral measurements were taken using a hand-held device, and the second included 18 post-cardiac surgery patients in which rectal measurements were taken using a rectal probe. Results: In study 1, Bland-Altman analysis showed a bias of -0.04°C [0.34-(-0.43)°C, 95% LOA] with a correlation of 99.4% (p < 0.001). In study 2, Bland-Altman analysis showed a bias of 0.0°C [0.27-(-0.28)°C, 95% LOA], and the correlation was 99.3% (p < 0.001). In both studies, stratifying patients based on BMI and skin tone showed high accordance in all sub-groups. Discussion: The wearable monitor showed high correlation with oral and core body temperature measurements in different clinical scenarios.
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Affiliation(s)
- Arik Eisenkraft
- Institute for Research in Military Medicine, Faculty of Medicine, The Hebrew University of Jerusalem and the Israel Defense Force Medical Corps, Jerusalem, Israel
- Biobeat Technologies Ltd., Petah Tikva, Israel
| | | | - Meir Fons
- Biobeat Technologies Ltd., Petah Tikva, Israel
| | | | | | | | - Roei Merin
- Biobeat Technologies Ltd., Petah Tikva, Israel
| | - Dean Nachman
- Institute for Research in Military Medicine, Faculty of Medicine, The Hebrew University of Jerusalem and the Israel Defense Force Medical Corps, Jerusalem, Israel
- Heart Institute, Hadassah Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel
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Zhang C, Liu H, Li X, Xu F, Li Z. Modularized synthetic biology enabled intelligent biosensors. Trends Biotechnol 2023; 41:1055-1065. [PMID: 36967259 DOI: 10.1016/j.tibtech.2023.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 02/27/2023] [Accepted: 03/06/2023] [Indexed: 03/29/2023]
Abstract
Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.
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Affiliation(s)
- Chao Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China
| | - Hao Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China
| | - Xiujun Li
- Department of Chemistry and Biochemistry, University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, USA
| | - Feng Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China.
| | - Zedong Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China; TFX Group-Xi'an Jiaotong University Institute of Life Health, Xi'an 710049, P.R. China.
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6
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van der Stam JA, Mestrom EHJ, Scheerhoorn J, Jacobs FENB, Nienhuijs S, Boer AK, van Riel NAW, de Morree HM, Bonomi AG, Scharnhorst V, Bouwman RA. The Accuracy of Wrist-Worn Photoplethysmogram-Measured Heart and Respiratory Rates in Abdominal Surgery Patients: Observational Prospective Clinical Validation Study. JMIR Perioper Med 2023; 6:e40474. [PMID: 36804173 PMCID: PMC9989911 DOI: 10.2196/40474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 01/12/2023] [Accepted: 01/31/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established. OBJECTIVE This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients. METHODS The accuracy of the wrist-worn PPG sensor was assessed in 62 post-abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m2). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy. RESULTS Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis. CONCLUSIONS The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained. TRIAL REGISTRATION ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127.
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Affiliation(s)
- Jonna A van der Stam
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - Eveline H J Mestrom
- Department of Anesthesiology, Intensive Care & Pain Medicine, Catharina Hospital, Eindhoven, Netherlands
| | - Jai Scheerhoorn
- Department of Surgery, Catharina Hospital, Eindhoven, Netherlands
| | - Fleur E N B Jacobs
- Department of Medical Physics, Catharina Hospital, Eindhoven, Netherlands
| | - Simon Nienhuijs
- Department of Surgery, Catharina Hospital, Eindhoven, Netherlands
| | - Arjen-Kars Boer
- Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - Natal A W van Riel
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands.,Department of Vascular Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Helma M de Morree
- Patient Care & Monitoring Department, Philips Research, Eindhoven, Netherlands
| | - Alberto G Bonomi
- Patient Care & Monitoring Department, Philips Research, Eindhoven, Netherlands
| | - Volkher Scharnhorst
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - R Arthur Bouwman
- Department of Anesthesiology, Intensive Care & Pain Medicine, Catharina Hospital, Eindhoven, Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
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7
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Xu J, Yan Z, Liu Q. Smartphone-Based Electrochemical Systems for Glucose Monitoring in Biofluids: A Review. Sensors (Basel) 2022; 22:s22155670. [PMID: 35957227 PMCID: PMC9371187 DOI: 10.3390/s22155670] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/19/2022] [Accepted: 07/22/2022] [Indexed: 05/12/2023]
Abstract
As a vital biomarker, glucose plays an important role in multiple physiological and pathological processes. Thus, glucose detection has become an important direction in the electrochemical analysis field. In order to realize more convenient, real-time, comfortable and accurate monitoring, smartphone-based portable, wearable and implantable electrochemical glucose monitoring is progressing rapidly. In this review, we firstly introduce technologies integrated in smartphones and the advantages of these technologies in electrochemical glucose detection. Subsequently, this overview illustrates the advances of smartphone-based portable, wearable and implantable electrochemical glucose monitoring systems in diverse biofluids over the last ten years (2012-2022). Specifically, some interesting and innovative technologies are highlighted. In the last section, after discussing the challenges in this field, we offer some future directions, such as application of advanced nanomaterials, novel power sources, simultaneous detection of multiple markers and a closed-loop system.
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8
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Galliani M, Ferrari LM, Ismailova E. Interdigitated Organic Sensor in Multimodal Facemask's Barrier Integrity and Wearer's Respiration Monitoring. Biosensors (Basel) 2022; 12:305. [PMID: 35624606 PMCID: PMC9138990 DOI: 10.3390/bios12050305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 05/03/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
Facemasks are used as a personal protective equipment in medical services. They became compulsory during the recent COVID-19 pandemic at large. Their barrier effectiveness during various daily activities over time has been the subject of much debate. We propose the fabrication of an organic sensor to monitor the integrity of surgical masks to ensure individuals' health and safety during their use. Inkjet printing of an interdigitated conducting polymer-based sensor on the inner layer of the mask proved to be an efficient and direct fabrication process to rapidly reach the end user. The sensor's integration happens without hampering the mask functionality and preserving its original air permeability. Its resistive response to humidity accumulation allows it to monitor the mask's wetting in use, providing a quantified way to track its barrier integrity and assist in its management. Additionally, it detects the user's respiration rate as a capacitive response to the exhaled humidity, essential in identifying breathing difficulties or a sign of an infection. Respiration evaluations during daily activities show outstanding performance in relation to unspecific motion artifacts and breathing resolution. This e-mask yields an integrated solution for home-based individual monitoring and an advanced protective equipment for healthcare professionals.
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Affiliation(s)
- Marina Galliani
- Mines Saint-Etienne, Centre CMP, Département BEL, 13541 Gardanne, France;
| | | | - Esma Ismailova
- Mines Saint-Etienne, Centre CMP, Département BEL, 13541 Gardanne, France;
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Zhang S, Tu T, Li T, Cai Y, Wang Z, Zhou Y, Wang D, Fang L, Ye X, Liang B. 3D MXene/PEDOT:PSS Composite Aerogel with a Controllable Patterning Property for Highly Sensitive Wearable Physical Monitoring and Robotic Tactile Sensing. ACS Appl Mater Interfaces 2022; 14:23877-23887. [PMID: 35467850 DOI: 10.1021/acsami.2c03350] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
MXene based composite conductive aerogels have been extensively investigated as sensitive materials for wearable pressure sensors owing to their effective 3D network microstructures and the excellent conductivity of MXene. In this work, we fabricated a 3D porous Ti3C2Tx MXene/poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) composite aerogel (MPCA) with a controllable patterning property utilizing the Cu-assisted electrogelation method. The prepared composite aerogel can be assembled into pressure sensors for wearable physical monitoring and high-resolution sensor microarrays for robotic tactile sensing. The multi-interactions between MXene and PEDOT:PSS enable the MPCA to have a stable 3D conductive network, which consequently enhances both the mechanical flexibility and the piezoresistive property of the MPCA. Thus, the fabricated pressure sensor demonstrating high sensitivity (26.65 kPa-1 within 0-2 kPa), fast response ability (106 ms), and excellent stability can be further applied for wearable physical monitoring. Moreover, due to the controllable patterning property of the electrogelation preparation method, a high-resolution pressure sensor microarray was successfully prepared as an artificial tactile interface, which can be attached to a robotic fingertip to directly recognize the tactile stimuli from human fingers and identify braille letters like human fingers. The proposed MPCA, endowed with a remarkable comprehensive property, particularly the highly sensitive sensing performance and controllable patterning property, demonstrates an enormous advantage and a great potentiality toward wearable electronics.
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Affiliation(s)
- Shanshan Zhang
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Tingting Tu
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Tianyu Li
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Yu Cai
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Zhaoyang Wang
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Yue Zhou
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Dong Wang
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Lu Fang
- College of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang 310027, PR China
| | - Xuesong Ye
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
| | - Bo Liang
- Biosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, PR China
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10
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Ansari S, Golbus JR, Tiba MH, McCracken B, Wang L, Aaronson KD, Ward KR, Najarian K, Oldham KR. Detection of Low Cardiac Index using a Polyvinylidene Fluoride-Based Wearable Ring and Convolutional Neural Networks. IEEE Sens J 2021; 21:14281-14289. [PMID: 34504397 PMCID: PMC8423366 DOI: 10.1109/jsen.2020.3022273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
This study investigated the use of a wearable ring made of polyvinylidene fluoride film to identify a low cardiac index (≤2 L/min). The waveform generated by the ring contains patterns that may be indicative of low blood pressure and/or high vascular resistance, both of which are markers of a low cardiac index. In particular, the waveform contains reflection waves whose timing and amplitude are correlated with pulse travel time and vascular resistance, respectively. Hence, the pattern of the waveform is expected to vary in response to changes in blood pressure and vascular resistance. By analyzing the morphology of the waveform, our aim was to create a tool to identify patients with low cardiac index. This was done using a convolutional neural network which was trained on data from animal models. The model was then tested on waveforms that were collected from patients undergoing pulmonary artery catheterization. The results indicate high accuracy in classifying patients with a low cardiac index, achieving an area under the receiver operating characteristics and precision-recall curves of 0.88 and 0.71, respectively.
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Affiliation(s)
- Sardar Ansari
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Jessica R Golbus
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109 USA
| | - Mohamad H Tiba
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Brendan McCracken
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Lu Wang
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Keith D Aaronson
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109 USA
| | - Kevin R Ward
- Department of Emergency Medicine and the Biomedical Engineering Department, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Kayvan Najarian
- Department of Computational Medicine and Bioinformatics, the Department of Emergency Medicine and the Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor, MI, 48109 USA
| | - Kenn R Oldham
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109 USA
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Billis A, Pandria N, Mouratoglou SA, Konstantinidis E, Bamidis P. Development of Cognitive and Physical Exercise Systems, Clinical Recordings, Large-Scale Data Analytics, and Virtual Coaching for Heart Failure Patients: Protocol for the BioTechCOACH-ForALL Project. JMIR Res Protoc 2020; 9:e17714. [PMID: 32364512 PMCID: PMC7235814 DOI: 10.2196/17714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 03/04/2020] [Accepted: 03/12/2020] [Indexed: 12/23/2022] Open
Abstract
Background Heart failure is a chronic disease affecting patient morbidity and mortality. Current guidelines for heart failure patient treatment are focused on improving their clinical status, functional capacity, and quality of life. However, these guidelines implement numerous instructions including medical treatment adherence, physical activity, and self-care management. The complexity of the therapeutic instructions makes them difficult to follow especially by older adults. Objective The challenge of this project is to (1) measure real-life adherence to a regular physical exercise program and (2) attempt to influence older adult patients with heart failure toward embracing a more physically active self-care lifestyle. Methods This research consists of two studies, including a lab experiment and a pragmatic evaluation of technology at patients’ homes. The lab experiment aims at exploring in an objective way (measuring neurophysiological responses to stimuli) patient engagement with different characteristics of virtual agents, while the home study is a 3-phase prospective study where the developed technology platform is tested by heart failure patients in their own home environments. Patients undergo evaluation of their physical activity and cognitive status using standard evaluation methods (6-minute walk test, questionnaires) and receive wearable devices to accurately measure everyday life activity levels (home study phases 1-3). During home study phases 2 and 3, exergames (serious games for physical exercise) to provide a physical exercise plan as a joyful activity are delivered to patients’ private households and e-coaching techniques are implemented in the final phase (home study phase 3) of the protocol, to influence patient attitudes toward a more healthy and recommended lifestyle. Results The trial is still ongoing. Recruitment is ongoing, and the project has progressed for some participants through phase 2 of the home study. The sample size for both studies is 28 participants; 10 have already been included in the study, and both baseline clinical and patient-reported outcome data are retrieved. Phases 2 and 3 of the home pilot study are expected to be completed within 6 months. Conclusions The main challenge of the project is the change of attitude of older age heart failure patients through an e-coaching system. Given the adoption of a cocreation and living lab approach and the main objective for real-life evaluation, the project is ready to react to any collected feedback, even during the implementation of the research plan. Clinical assessment and objective evaluation are expected to provide all required information for reliable findings. Trial Registration ClinicalTrials.gov NCT03877328; https://clinicaltrials.gov/ct2/show/NCT03877328 International Registered Report Identifier (IRRID) DERR1-10.2196/17714
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Affiliation(s)
- Antonis Billis
- Laboratory of Medical Physics, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Niki Pandria
- Laboratory of Medical Physics, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Sophia-Anastasia Mouratoglou
- Laboratory of Medical Physics, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Evdokimos Konstantinidis
- Laboratory of Medical Physics, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Panagiotis Bamidis
- Laboratory of Medical Physics, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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Jovanov E. Wearables Meet IoT: Synergistic Personal Area Networks (SPANs). Sensors (Basel) 2019; 19:E4295. [PMID: 31623393 PMCID: PMC6806600 DOI: 10.3390/s19194295] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 09/19/2019] [Accepted: 10/01/2019] [Indexed: 02/05/2023]
Abstract
Wearable monitoring and mobile health (mHealth) revolutionized healthcare diagnostics and delivery, while the exponential increase of deployed "things" in the Internet of things (IoT) transforms our homes and industries. "Things" with embedded activity and vital sign sensors that we refer to as "smart stuff" can interact with wearable and ambient sensors. A dynamic, ad-hoc personal area network can span multiple domains and facilitate processing in synergistic personal area networks-SPANs. The synergy of information from multiple sensors can provide: (a) New information that cannot be generated from existing data alone, (b) user identification, (c) more robust assessment of physiological signals, and (d) automatic annotation of events/records. In this paper, we present possible new applications of SPANs and results of feasibility studies. Preliminary tests indicate that users interact with smart stuff-in our case, a smart water bottle-dozens of times a day and sufficiently long to collect vital signs of the users. Synergistic processing of sensors from the smartwatch and objects of everyday use may provide user identification and assessment of new parameters that individual sensors could not generate, such as pulse wave velocity (PWV) and blood pressure. As a result, SPANs facilitate seamless monitoring and annotation of vital signs dozens of times per day, every day, every time the smart object is used, without additional setup of sensors and initiation of measurements. SPANs creates a dynamic "opportunistic bubble" for ad-hoc integration with other sensors of interest around the user, wherever they go. Continuous long-term monitoring of user's activity and vital signs can provide better diagnostic procedures and personalized feedback to motivate a proactive approach to health and wellbeing.
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Affiliation(s)
- Emil Jovanov
- Electrical and Computer Engineering Department, The University of Alabama in Huntsville, Huntsville, AL 35899, USA.
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Caduff A, Zanon M, Zakharov P, Mueller M, Talary M, Krebs A, Stahel WA, Donath M. First Experiences With a Wearable Multisensor in an Outpatient Glucose Monitoring Study, Part I: The Users' View. J Diabetes Sci Technol 2018; 12:562-568. [PMID: 29332423 PMCID: PMC6154235 DOI: 10.1177/1932296817750932] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Extensive past work showed that noninvasive continuous glucose monitoring with a wearable Multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions. METHODS To test previous findings also in uncontrolled in-clinic and outpatient conditions, a long-term study has been conducted to collect Multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking Multisensor data to glucose applied to estimate glucose trends noninvasively. The operation of a digital log book, daily semiautomated data transfer and at least 10 daily SMBG values were requested from the patient. RESULTS Results showed that the Multisensor is capable of indicating glucose trends. It can do so in 9 out of 10 cases either correctly or with one level of discrepancy. This means that in 90% of all cases the Multisensor shows the glucose dynamic to rapidly increase or at least increase. CONCLUSIONS The Multisensor and the algorithmic routine used in controlled conditions can track glucose trends in all patients, also in uncontrolled conditions. Training of the patient proved to be essential. The workload imposed on patients was significant and should be reduced in the next step with further automation. The feature of glucose trend indication was welcomed and very much appreciated by patients; this value creation makes a strong case for the justification of wearing a wearable.
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Affiliation(s)
- Andreas Caduff
- Biovotion AG, Zurich, Switzerland
- Andreas Caduff, PhD, Biovotion AG, Kreuzstrasse 2, Zurich 8008, Switzerland.
| | | | | | | | | | | | | | - Marc Donath
- Clinic for Endocrinology and Diabetes, University Hospital Basel, Basel, Switzerland
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