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Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics

Non-contact human-computer interactions (HCI) based on hand gestures have been widely investigated. Here, we present a novel method to locate the real-time position of the hand using the electrostatics of the human body. This method has many advantages, including a delay of less than one millisecond...

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Detalles Bibliográficos
Autores principales: Tang, Kai, Li, Pengfei, Wang, Chuang, Wang, Yifei, Chen, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021916/
https://www.ncbi.nlm.nih.gov/pubmed/29882881
http://dx.doi.org/10.3390/s18061677
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author Tang, Kai
Li, Pengfei
Wang, Chuang
Wang, Yifei
Chen, Xi
author_facet Tang, Kai
Li, Pengfei
Wang, Chuang
Wang, Yifei
Chen, Xi
author_sort Tang, Kai
collection PubMed
description Non-contact human-computer interactions (HCI) based on hand gestures have been widely investigated. Here, we present a novel method to locate the real-time position of the hand using the electrostatics of the human body. This method has many advantages, including a delay of less than one millisecond, low cost, and does not require a camera or wearable devices. A formula is first created to sense array signals with five spherical electrodes. Next, a solving algorithm for the real-time measured hand position is introduced and solving equations for three-dimensional coordinates of hand position are obtained. A non-contact real-time hand position sensing system was established to perform verification experiments, and the principle error of the algorithm and the systematic noise were also analyzed. The results show that this novel technology can determine the dynamic parameters of hand movements with good robustness to meet the requirements of complicated HCI.
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spelling pubmed-60219162018-07-02 Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics Tang, Kai Li, Pengfei Wang, Chuang Wang, Yifei Chen, Xi Sensors (Basel) Article Non-contact human-computer interactions (HCI) based on hand gestures have been widely investigated. Here, we present a novel method to locate the real-time position of the hand using the electrostatics of the human body. This method has many advantages, including a delay of less than one millisecond, low cost, and does not require a camera or wearable devices. A formula is first created to sense array signals with five spherical electrodes. Next, a solving algorithm for the real-time measured hand position is introduced and solving equations for three-dimensional coordinates of hand position are obtained. A non-contact real-time hand position sensing system was established to perform verification experiments, and the principle error of the algorithm and the systematic noise were also analyzed. The results show that this novel technology can determine the dynamic parameters of hand movements with good robustness to meet the requirements of complicated HCI. MDPI 2018-05-23 /pmc/articles/PMC6021916/ /pubmed/29882881 http://dx.doi.org/10.3390/s18061677 Text en © 2018 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
Tang, Kai
Li, Pengfei
Wang, Chuang
Wang, Yifei
Chen, Xi
Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title_full Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title_fullStr Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title_full_unstemmed Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title_short Real-Time Hand Position Sensing Technology Based on Human Body Electrostatics
title_sort real-time hand position sensing technology based on human body electrostatics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021916/
https://www.ncbi.nlm.nih.gov/pubmed/29882881
http://dx.doi.org/10.3390/s18061677
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AT wangyifei realtimehandpositionsensingtechnologybasedonhumanbodyelectrostatics
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