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Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor
Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199135/ https://www.ncbi.nlm.nih.gov/pubmed/34071372 http://dx.doi.org/10.3390/s21113750 |
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author | Jeong, Yeon-Keun Baek, Kwang-Ryul |
author_facet | Jeong, Yeon-Keun Baek, Kwang-Ryul |
author_sort | Jeong, Yeon-Keun |
collection | PubMed |
description | Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters can be used to determine asymmetric walking. The spatiotemporal parameter has the disadvantage that it does not consider the influence of the diversity of patterns and the walking speed. Therefore, in this paper, we propose a method to analyze asymmetric walking using Dynamic Time Warping (DTW) distance, a time series analysis method. The DTW distance was obtained by combining gyroscope data and pressure data. The experiment was carried out by performing symmetrical walking and asymmetrical walking, and asymmetric walking was performed as a simulation of hemiplegic walking by fixing one ankle using an auxiliary device. The proposed method was compared with the existing asymmetric gait analysis method. As a result of the experiment, a p-value lower than 0.05 was obtained, which proved that there was a statistically significant difference. |
format | Online Article Text |
id | pubmed-8199135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81991352021-06-14 Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor Jeong, Yeon-Keun Baek, Kwang-Ryul Sensors (Basel) Article Walking is one of the most basic human activities. Various diseases may be caused by abnormal walking, and abnormal walking is mostly caused by disease. There are various characteristics of abnormal walking, but in general, it can be judged as asymmetric walking. Generally, spatiotemporal parameters can be used to determine asymmetric walking. The spatiotemporal parameter has the disadvantage that it does not consider the influence of the diversity of patterns and the walking speed. Therefore, in this paper, we propose a method to analyze asymmetric walking using Dynamic Time Warping (DTW) distance, a time series analysis method. The DTW distance was obtained by combining gyroscope data and pressure data. The experiment was carried out by performing symmetrical walking and asymmetrical walking, and asymmetric walking was performed as a simulation of hemiplegic walking by fixing one ankle using an auxiliary device. The proposed method was compared with the existing asymmetric gait analysis method. As a result of the experiment, a p-value lower than 0.05 was obtained, which proved that there was a statistically significant difference. MDPI 2021-05-28 /pmc/articles/PMC8199135/ /pubmed/34071372 http://dx.doi.org/10.3390/s21113750 Text en © 2021 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 | Article Jeong, Yeon-Keun Baek, Kwang-Ryul Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title | Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title_full | Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title_fullStr | Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title_full_unstemmed | Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title_short | Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor |
title_sort | asymmetric gait analysis using a dtw algorithm with combined gyroscope and pressure sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199135/ https://www.ncbi.nlm.nih.gov/pubmed/34071372 http://dx.doi.org/10.3390/s21113750 |
work_keys_str_mv | AT jeongyeonkeun asymmetricgaitanalysisusingadtwalgorithmwithcombinedgyroscopeandpressuresensor AT baekkwangryul asymmetricgaitanalysisusingadtwalgorithmwithcombinedgyroscopeandpressuresensor |