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Abnormal Gait Detection Using Wearable Hall-Effect Sensors
Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the op...
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/PMC7915068/ https://www.ncbi.nlm.nih.gov/pubmed/33572170 http://dx.doi.org/10.3390/s21041206 |
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author | Chheng, Courtney Wilson, Denise |
author_facet | Chheng, Courtney Wilson, Denise |
author_sort | Chheng, Courtney |
collection | PubMed |
description | Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury. |
format | Online Article Text |
id | pubmed-7915068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79150682021-03-01 Abnormal Gait Detection Using Wearable Hall-Effect Sensors Chheng, Courtney Wilson, Denise Sensors (Basel) Article Abnormalities and irregularities in walking (gait) are predictors and indicators of both disease and injury. Gait has traditionally been monitored and analyzed in clinical settings using complex video (camera-based) systems, pressure mats, or a combination thereof. Wearable gait sensors offer the opportunity to collect data in natural settings and to complement data collected in clinical settings, thereby offering the potential to improve quality of care and diagnosis for those whose gait varies from healthy patterns of movement. This paper presents a gait monitoring system designed to be worn on the inner knee or upper thigh. It consists of low-power Hall-effect sensors positioned on one leg and a compact magnet positioned on the opposite leg. Wireless data collected from the sensor system were used to analyze stride width, stride width variability, cadence, and cadence variability for four different individuals engaged in normal gait, two types of abnormal gait, and two types of irregular gait. Using leg gap variability as a proxy for stride width variability, 81% of abnormal or irregular strides were accurately identified as different from normal stride. Cadence was surprisingly 100% accurate in identifying strides which strayed from normal, but variability in cadence provided no useful information. This highly sensitive, non-contact Hall-effect sensing method for gait monitoring offers the possibility for detecting visually imperceptible gait variability in natural settings. These nuanced changes in gait are valuable for predicting early stages of disease and also for indicating progress in recovering from injury. MDPI 2021-02-09 /pmc/articles/PMC7915068/ /pubmed/33572170 http://dx.doi.org/10.3390/s21041206 Text en © 2021 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 Chheng, Courtney Wilson, Denise Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title | Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title_full | Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title_fullStr | Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title_full_unstemmed | Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title_short | Abnormal Gait Detection Using Wearable Hall-Effect Sensors |
title_sort | abnormal gait detection using wearable hall-effect sensors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7915068/ https://www.ncbi.nlm.nih.gov/pubmed/33572170 http://dx.doi.org/10.3390/s21041206 |
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