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Tao D, Xie C, Jaffrezic-Renault N, Guo Z. Flexible and wearable electrochemical sensors for health and safety monitoring. Talanta 2025; 291:127863. [PMID: 40043375 DOI: 10.1016/j.talanta.2025.127863] [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: 12/26/2024] [Revised: 02/24/2025] [Accepted: 02/28/2025] [Indexed: 03/24/2025]
Abstract
Environmental safety monitoring is a crucial process that involves continuous and systematic observation and analysis of various pollutants in the environment to ensure its quality and safety. This monitoring encompasses a wide range of areas, including physical indicator monitoring (pertaining to parameters such as temperature, humidity, and wind speed), chemical indicator monitoring (focused on detecting harmful substances in environmental media such as air, water, and soil), and ecosystem monitoring (including biodiversity assessments and judgments on the health status of ecosystems). This review delves deeply into the significant advancements achieved in the field of flexible and wearable electrochemical sensors (FWESs) over the past fifteen years (from 2010 to 2024). It emphasizes the broad application of these sensors in health and environmental safety monitoring, with health monitoring primarily focusing on exhaled breath and sweat, and environmental monitoring covering temperature, humidity, and pollutants in air and water. By seamlessly integrating electrochemical principles, advanced sensor manufacturing technologies, and sensor functionalization, FWESs have opened up new avenues for non-invasive real-time monitoring of human health and environmental safety. This review highlights key developments in sensor structures, including flexible substrates, printed electrodes, and active materials. It also underscores the remarkable progress made in healthcare and environmental monitoring through the utilization of FWES. Despite these promising advancements, this emerging field still faces numerous challenges, such as improving sensor accuracy, enhancing durability, and reducing costs. The review concludes by discussing the future directions in this field, including ongoing research efforts aimed at overcoming these challenges and expanding the applications of FWESs in various sectors.
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Affiliation(s)
- Dan Tao
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou, 561113, China; Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 561113, China
| | - Chun Xie
- School of Public Health, The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou, 561113, China; Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 561113, China
| | | | - Zhenzhong Guo
- Hubei Province Key Laboratory of Occupational Hazard Identification and Control, School of Public Health, Faculty of Medicine, Wuhan University of Science and Technology, Wuhan, 430065, China.
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Chen S, Fan S, Qiao Z, Wu Z, Lin B, Li Z, Riegler MA, Wong MYH, Opheim A, Korostynska O, Nielsen KM, Glott T, Martinsen ACT, Telle-Hansen VH, Lim CT. Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2025; 37:e2500412. [PMID: 40167502 DOI: 10.1002/adma.202500412] [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: 01/07/2025] [Revised: 03/14/2025] [Indexed: 04/02/2025]
Abstract
Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a shift from traditional, hospital-centered healthcare to a more decentralized, patient-centric model, where wearable sensors can collect real-time physiological data, provide deep analysis of these data streams, and generate actionable insights for point-of-care precise diagnostics and personalized therapy. Despite rapid advancements in smart materials, machine learning, and wearable sensing technologies, there is a lack of comprehensive reviews that systematically examine the intersection of these fields. This review addresses this gap, providing a critical analysis of wearable sensing technologies empowered by smart advanced materials and artificial Intelligence. The state-of-the-art smart materials-including self-healing, metamaterials, and responsive materials-that enhance sensor functionality are first examined. Advanced machine learning methodologies integrated into wearable devices are discussed, and their role in biomedical applications is highlighted. The combined impact of wearable sensors, empowered by smart materials and machine learning, and their applications in intelligent diagnostics and therapeutics are also examined. Finally, existing challenges, including technical and compliance issues, information security concerns, and regulatory considerations are addressed, and future directions for advancing intelligent healthcare are proposed.
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Affiliation(s)
- Shuwen Chen
- Institute of Medical Equipment Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Shicheng Fan
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Zheng Qiao
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Zixiong Wu
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Baobao Lin
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Zhijie Li
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
| | - Michael A Riegler
- Simula Metropolitan Center for Digital Engineering, Oslo, 0167, Norway
| | | | - Arve Opheim
- Sunnaas Rehabilitation Hospital, Bjoernemyr, 1453, Norway
- Institute of Neuroscience and Physiology, Unit for Rehabilitation Medicine, University of Gothenburg, Gothenburg, 413 45, Sweden
| | - Olga Korostynska
- Department of Mechanical, Electronic and Chemical Engineering (MEK), Faculty of Technology, Art, and Design, TKD, Oslo Metropolitan University, OsloMet, Oslo, 0166, Norway
| | - Kaare Magne Nielsen
- Department of Life Science and Health, Faculty of Health Sciences, Oslo Metropolitan University, OsloMet, Oslo, 0130, Norway
- Intelligent Health, Faculty of Health Sciences and Faculty of Technology, Art and Design, Oslo Metropolitan University, OsloMet, Oslo, 0130, Norway
| | - Thomas Glott
- Sunnaas Rehabilitation Hospital, Bjoernemyr, 1453, Norway
| | - Anne Catrine T Martinsen
- Sunnaas Rehabilitation Hospital, Bjoernemyr, 1453, Norway
- Department of Rehabilitation Science and Health Technology, Faculty of Health Sciences, Oslo Metropolitan University, OsloMet, Oslo, 0130, Norway
| | - Vibeke H Telle-Hansen
- Intelligent Health, Faculty of Health Sciences and Faculty of Technology, Art and Design, Oslo Metropolitan University, OsloMet, Oslo, 0130, Norway
- Department of Nursing and Health Promotion, Faculty of Health Sciences, Oslo Metropolitan University, OsloMet, Oslo, 0130, Norway
| | - Chwee Teck Lim
- Department of Biomedical Engineering, National University of Singapore, Singapore, 117583, Singapore
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore, 119276, Singapore
- Mechanobiology Institute, National University of Singapore, Singapore, 117411, Singapore
- Institute for Functional Intelligent Materials, National University of Singapore, Singapore, 117544, Singapore
- SIA-NUS Digital Aviation Corp Lab, National University of Singapore, Singapore, 117602, Singapore
- Institute for Digital Molecular Analytics and Science, Nanyang Technological University, Singapore, 636921, Singapore
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Kwon DA, Lee S, Kim CY, Kang I, Park S, Jeong JW. Body-temperature softening electronic ink for additive manufacturing of transformative bioelectronics via direct writing. SCIENCE ADVANCES 2024; 10:eadn1186. [PMID: 38416839 PMCID: PMC10901467 DOI: 10.1126/sciadv.adn1186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 01/29/2024] [Indexed: 03/01/2024]
Abstract
Mechanically transformative electronic systems (TESs) built using gallium have emerged as an innovative class of electronics due to their ability to switch between rigid and flexible states, thus expanding the versatility of electronics. However, the challenges posed by gallium's high surface tension and low viscosity have substantially hindered manufacturability, limiting high-resolution patterning of TESs. To address this challenge, we introduce a stiffness-tunable gallium-copper composite ink capable of direct ink write printing of intricate TES circuits, offering high-resolution (~50 micrometers) patterning, high conductivity, and bidirectional soft-rigid convertibility. These features enable transformative bioelectronics with design complexity akin to traditional printed circuit boards. These TESs maintain rigidity at room temperature for easy handling but soften and conform to curvilinear tissue surfaces at body temperature, adapting to dynamic tissue deformations. The proposed ink with direct ink write printing makes TES manufacturing simple and versatile, opening possibilities in wearables, implantables, consumer electronics, and robotics.
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Affiliation(s)
- Do A Kwon
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Simok Lee
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Choong Yeon Kim
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Inho Kang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Steve Park
- Department of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon 34141, Republic of Korea
| | - Jae-Woong Jeong
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon 34141, Republic of Korea
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