Design Strategies for Strain-Insensitive Wearable Healthcare Sensors and Perspective Based on the Seebeck Coefficient
KAUST DepartmentKing Abdullah University of Science and Technology (KAUST) Physical Sciences and Engineering Division (PSE) Mechanics of Composites for Energy and Mobility Lab, Thuwal 23955-6900, Saudi Arabia
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberBAS/1/1315-01-01
Permanent link to this recordhttp://hdl.handle.net/10754/681581
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AbstractLarge healthcare markets have been created in highly developed economies to improve the quality of life. Wearable healthcare sensors are attracting considerable interest because of their 24 h real-time monitoring capability, which make them useful in the detection of potential diseases. To guide the diagnosis, these sensors are designed to monitor various physical (e.g., pressure, temperature, strain, touch, bioelectricity, etc...) or chemical (e.g., glucose, oxygen, bacteria, viruses, proteins, etc...) quantities. In order to be comfortable to wear for a longer period of time, the sensors must be made with good stretchability to conformably deform with human organs. However, high stretchability always brings the problem that the measurement is very often polluted by the deformation of the substrate, making the data unreliable. According to each the sensor mechanism, multiple strain-insensitive design strategies compatible with large deformations of the human body are discussed and the performance of these strategies are comprehensively analyzed. Then, how the intrinsic strain insensitivity of the Seebeck coefficient of nanomaterial percolation networks can define an alternative promising strategy is demostrated. Finally, the outlooks for future research and challenges in realizing strain-insensitive sensors by applying the Seebeck effect are reported.
CitationXin, Y., Zhou, J., Nesser, H., & Lubineau, G. (2022). Design Strategies for Strain-Insensitive Wearable Healthcare Sensors and Perspective Based on the Seebeck Coefficient. Advanced Electronic Materials, 2200534. Portico. https://doi.org/10.1002/aelm.202200534
SponsorsThe research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST), under award number BAS/1/1315-01-01.
JournalAdvanced Electronic Materials
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