A Self‐Powered Body Motion Sensing Network Integrated with Multiple Triboelectric Fabrics for Biometric Gait Recognition and Auxiliary Rehabilitation Training
Chinese Academy of Sciences · Beijing Institute of Nanoenergy and Nanosystems · +4 more institutions
Abstract
Abstract Gait analysis provides a convenient strategy for the diagnosis and rehabilitation assessment of diseases of skeletal, muscular, and neurological systems. However, challenges remain in current gait recognition methods due to the drawbacks of complex systems, high cost, affecting natural gait, and one‐size‐fits‐all model. Here, a highly integrated gait recognition system composed of a self‐powered multi‐point body motion sensing network (SMN) based on full textile structure is demonstrated. By combining of newly developed energy harvesting technology of triboelectric nanogenerator (TENG) and traditional textile manufacturing process, SMN not only ensures high pressure response sensitivity up to 1.5 V…
Citation impact
- FWCI
- 18.47
- Percentile
- 100%
- References
- 38
Authors
9- CWChuanhui Wei
Chinese Academy of Sciences, Beijing Institute of Nanoenergy and Nanosystems, University of Chinese Academy of Sciences
- RCRenwei Cheng
Chinese Academy of Sciences, Beijing Institute of Nanoenergy and Nanosystems, University of Chinese Academy of Sciences
- CNChuan Ning
Chinese Academy of Sciences, Zhengzhou University, Beijing Institute of Nanoenergy and Nanosystems
- XWXuyang Wei
Harbin University of Science and Technology
- XPXiao Peng
Chinese Academy of Sciences, Beijing Institute of Nanoenergy and Nanosystems, University of Chinese Academy of Sciences
Topics & keywords
- Gait
- Flexibility (engineering)
- Computer science
- Rehabilitation
- Biometrics
- Nanogenerator
- Orthotics
- Process (computing)
- Affordable and clean energy