To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait...To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is proposed.The main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance.Exploiting the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait information.Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status.Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.展开更多
基金supported by the Xi’an Science and Technology Plan Project (No.2020KJRC0108).
文摘To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly,a portable and lowcost triboelectric nanogenerator(TENG)-based self-powered sensor for human gait monitoring is proposed.The main fabrication materials of the TENG are polytetrafluoroethylene(PTFE)film,aluminum(Al)foil,and polyimide(PI)film,where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance.Exploiting the ability of TENGs to monitor changes in environmental conditions,a self-powered sensor based on the TENG is placed in an insole to collect gait information.Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals,the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status.Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%,demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.
