Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method
Accurate estimation of gait parameters is essential for obtaining quantitative information on motor deficits in Parkinson’s disease and other neurodegenerative diseases, which helps determine disease progression and therapeutic interventions. Due to the demand for high accuracy, unobtrusiv...
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doaj-4644c166f6774e45b130744c5d6aaf462020-11-25T00:50:03ZengMDPI AGSensors1424-82202018-05-01186173710.3390/s18061737s18061737Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based MethodMengxuan Li0Pengfei Li1Shanshan Tian2Kai Tang3Xi Chen4State Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Mechatronics Engineering and Control, Beijing Institute of Technology, Beijing 100081, ChinaAccurate estimation of gait parameters is essential for obtaining quantitative information on motor deficits in Parkinson’s disease and other neurodegenerative diseases, which helps determine disease progression and therapeutic interventions. Due to the demand for high accuracy, unobtrusive measurement methods such as optical motion capture systems, foot pressure plates, and other systems have been commonly used in clinical environments. However, the high cost of existing lab-based methods greatly hinders their wider usage, especially in developing countries. In this study, we present a low-cost, noncontact, and an accurate temporal gait parameters estimation method by sensing and analyzing the electrostatic field generated from human foot stepping. The proposed method achieved an average 97% accuracy on gait phase detection and was further validated by comparison to the foot pressure system in 10 healthy subjects. Two results were compared using the Pearson coefficient r and obtained an excellent consistency (r = 0.99, p < 0.05). The repeatability of the purposed method was calculated between days by intraclass correlation coefficients (ICC), and showed good test-retest reliability (ICC = 0.87, p < 0.01). The proposed method could be an affordable and accurate tool to measure temporal gait parameters in hospital laboratories and in patients’ home environments.http://www.mdpi.com/1424-8220/18/6/1737electrostatic field sensinggait measurementtemporal parameters |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mengxuan Li Pengfei Li Shanshan Tian Kai Tang Xi Chen |
spellingShingle |
Mengxuan Li Pengfei Li Shanshan Tian Kai Tang Xi Chen Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method Sensors electrostatic field sensing gait measurement temporal parameters |
author_facet |
Mengxuan Li Pengfei Li Shanshan Tian Kai Tang Xi Chen |
author_sort |
Mengxuan Li |
title |
Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method |
title_short |
Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method |
title_full |
Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method |
title_fullStr |
Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method |
title_full_unstemmed |
Estimation of Temporal Gait Parameters Using a Human Body Electrostatic Sensing-Based Method |
title_sort |
estimation of temporal gait parameters using a human body electrostatic sensing-based method |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-05-01 |
description |
Accurate estimation of gait parameters is essential for obtaining quantitative information on motor deficits in Parkinson’s disease and other neurodegenerative diseases, which helps determine disease progression and therapeutic interventions. Due to the demand for high accuracy, unobtrusive measurement methods such as optical motion capture systems, foot pressure plates, and other systems have been commonly used in clinical environments. However, the high cost of existing lab-based methods greatly hinders their wider usage, especially in developing countries. In this study, we present a low-cost, noncontact, and an accurate temporal gait parameters estimation method by sensing and analyzing the electrostatic field generated from human foot stepping. The proposed method achieved an average 97% accuracy on gait phase detection and was further validated by comparison to the foot pressure system in 10 healthy subjects. Two results were compared using the Pearson coefficient r and obtained an excellent consistency (r = 0.99, p < 0.05). The repeatability of the purposed method was calculated between days by intraclass correlation coefficients (ICC), and showed good test-retest reliability (ICC = 0.87, p < 0.01). The proposed method could be an affordable and accurate tool to measure temporal gait parameters in hospital laboratories and in patients’ home environments. |
topic |
electrostatic field sensing gait measurement temporal parameters |
url |
http://www.mdpi.com/1424-8220/18/6/1737 |
work_keys_str_mv |
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1725249655383523328 |