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Self-Powered Smart Insole for Monitoring Human Gait Signals
With the rapid development of low-power consumption wireless sensors and wearable electronics, harvesting energy from human motion to enable self-powered sensing is becoming desirable. Herein, a pair of smart insoles integrated with piezoelectric poly(vinylidene fluoride) (PVDF) nanogenerators (NGs)...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960832/ https://www.ncbi.nlm.nih.gov/pubmed/31817067 http://dx.doi.org/10.3390/s19245336 |
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author | Wang, Wei Cao, Junyi Yu, Jian Liu, Rong Bowen, Chris R. Liao, Wei-Hsin |
author_facet | Wang, Wei Cao, Junyi Yu, Jian Liu, Rong Bowen, Chris R. Liao, Wei-Hsin |
author_sort | Wang, Wei |
collection | PubMed |
description | With the rapid development of low-power consumption wireless sensors and wearable electronics, harvesting energy from human motion to enable self-powered sensing is becoming desirable. Herein, a pair of smart insoles integrated with piezoelectric poly(vinylidene fluoride) (PVDF) nanogenerators (NGs) are fabricated to simultaneously harvest energy from human motion and monitor human gait signals. Multi-target magnetron sputtering technology is applied to form the aluminum electrode layers on the surface of the PVDF film and the self-powered insoles are fabricated through advanced 3D seamless flat-bed knitting technology. Output responses of the NGs are measured at different motion speeds and a maximum value of 41 V is obtained, corresponding to an output power of 168.1 μW. By connecting one NG with an external circuit, the influence of external resistance, capacitor, and motion speed on the charging characteristics of the system is systematically investigated. To demonstrate the potential of the smart insoles for monitoring human gait signals, two subjects were asked to walk on a treadmill at different speeds or with a limp. The results show that one can clearly distinguish walking with a limp from regular slow, normal, and fast walking states by using multiscale entropy analysis of the stride intervals. |
format | Online Article Text |
id | pubmed-6960832 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69608322020-01-24 Self-Powered Smart Insole for Monitoring Human Gait Signals Wang, Wei Cao, Junyi Yu, Jian Liu, Rong Bowen, Chris R. Liao, Wei-Hsin Sensors (Basel) Article With the rapid development of low-power consumption wireless sensors and wearable electronics, harvesting energy from human motion to enable self-powered sensing is becoming desirable. Herein, a pair of smart insoles integrated with piezoelectric poly(vinylidene fluoride) (PVDF) nanogenerators (NGs) are fabricated to simultaneously harvest energy from human motion and monitor human gait signals. Multi-target magnetron sputtering technology is applied to form the aluminum electrode layers on the surface of the PVDF film and the self-powered insoles are fabricated through advanced 3D seamless flat-bed knitting technology. Output responses of the NGs are measured at different motion speeds and a maximum value of 41 V is obtained, corresponding to an output power of 168.1 μW. By connecting one NG with an external circuit, the influence of external resistance, capacitor, and motion speed on the charging characteristics of the system is systematically investigated. To demonstrate the potential of the smart insoles for monitoring human gait signals, two subjects were asked to walk on a treadmill at different speeds or with a limp. The results show that one can clearly distinguish walking with a limp from regular slow, normal, and fast walking states by using multiscale entropy analysis of the stride intervals. MDPI 2019-12-04 /pmc/articles/PMC6960832/ /pubmed/31817067 http://dx.doi.org/10.3390/s19245336 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Wei Cao, Junyi Yu, Jian Liu, Rong Bowen, Chris R. Liao, Wei-Hsin Self-Powered Smart Insole for Monitoring Human Gait Signals |
title | Self-Powered Smart Insole for Monitoring Human Gait Signals |
title_full | Self-Powered Smart Insole for Monitoring Human Gait Signals |
title_fullStr | Self-Powered Smart Insole for Monitoring Human Gait Signals |
title_full_unstemmed | Self-Powered Smart Insole for Monitoring Human Gait Signals |
title_short | Self-Powered Smart Insole for Monitoring Human Gait Signals |
title_sort | self-powered smart insole for monitoring human gait signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6960832/ https://www.ncbi.nlm.nih.gov/pubmed/31817067 http://dx.doi.org/10.3390/s19245336 |
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