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A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes

In order to develop a non-contact and simple gesture recognition technology, a recognition method with a charge induction array of nine electrodes is proposed. Firstly, the principle of signal acquisition based on charge induction is introduced, and the whole system is given. Secondly, the recogniti...

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Detalles Bibliográficos
Autores principales: Qian, Hao, Chi, Yangbin, Dong, Zining, Yan, Feng, Zhang, Limin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838362/
https://www.ncbi.nlm.nih.gov/pubmed/35161902
http://dx.doi.org/10.3390/s22031158
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author Qian, Hao
Chi, Yangbin
Dong, Zining
Yan, Feng
Zhang, Limin
author_facet Qian, Hao
Chi, Yangbin
Dong, Zining
Yan, Feng
Zhang, Limin
author_sort Qian, Hao
collection PubMed
description In order to develop a non-contact and simple gesture recognition technology, a recognition method with a charge induction array of nine electrodes is proposed. Firstly, the principle of signal acquisition based on charge induction is introduced, and the whole system is given. Secondly, the recognition algorithms, including the pre-processing algorithm and back propagation neural network (BPNN) algorithm, are given to recognize three input modes of hand gestures, digital input, direction input and key input, respectively. Finally, experiments of three input modes of hand gestures are carried out, and the recognition accuracy is 97.2%, 94%, and 100% for digital input, direction input, and key input, respectively. The outstanding characteristic of this method is the real-time recognition of three hand gestures in the distance of 2 cm without the need of wearing any device, as well as being low cost and easy to implement.
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spelling pubmed-88383622022-02-13 A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes Qian, Hao Chi, Yangbin Dong, Zining Yan, Feng Zhang, Limin Sensors (Basel) Communication In order to develop a non-contact and simple gesture recognition technology, a recognition method with a charge induction array of nine electrodes is proposed. Firstly, the principle of signal acquisition based on charge induction is introduced, and the whole system is given. Secondly, the recognition algorithms, including the pre-processing algorithm and back propagation neural network (BPNN) algorithm, are given to recognize three input modes of hand gestures, digital input, direction input and key input, respectively. Finally, experiments of three input modes of hand gestures are carried out, and the recognition accuracy is 97.2%, 94%, and 100% for digital input, direction input, and key input, respectively. The outstanding characteristic of this method is the real-time recognition of three hand gestures in the distance of 2 cm without the need of wearing any device, as well as being low cost and easy to implement. MDPI 2022-02-03 /pmc/articles/PMC8838362/ /pubmed/35161902 http://dx.doi.org/10.3390/s22031158 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Qian, Hao
Chi, Yangbin
Dong, Zining
Yan, Feng
Zhang, Limin
A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title_full A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title_fullStr A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title_full_unstemmed A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title_short A Gesture Recognition Method with a Charge Induction Array of Nine Electrodes
title_sort gesture recognition method with a charge induction array of nine electrodes
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838362/
https://www.ncbi.nlm.nih.gov/pubmed/35161902
http://dx.doi.org/10.3390/s22031158
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