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Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models
Women often wear high-heeled shoes for professional or esthetic reasons. However, high-heeled shoes can cause discomfort and injury and can change the body’s center of gravity when maintaining balance. This study developed an assessment system for predicting the maximal safe range for heel height by...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9103558/ https://www.ncbi.nlm.nih.gov/pubmed/35591131 http://dx.doi.org/10.3390/s22093442 |
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author | Hwang, Yi-Ting Lee, Si-Huei Lin, Bor-Shing |
author_facet | Hwang, Yi-Ting Lee, Si-Huei Lin, Bor-Shing |
author_sort | Hwang, Yi-Ting |
collection | PubMed |
description | Women often wear high-heeled shoes for professional or esthetic reasons. However, high-heeled shoes can cause discomfort and injury and can change the body’s center of gravity when maintaining balance. This study developed an assessment system for predicting the maximal safe range for heel height by recording the plantar pressure of participants’ feet by using force-sensing resistor (FSR) sensors and conducting analyses using regression models. Specifically, 100 young healthy women stood on an adjustable platform while physicians estimated the maximal safe height of high-heeled shoes. The collected FSR data combined with and without personal features were analyzed using regression models. The experimental results showed that the regression model based on the pressure data for the right foot had better predictive power than that based on data for the left foot, regardless of the module. The model with two heights had higher predictive power than that with a single height. Furthermore, adding personal features under the condition of two heights afforded the best predictive effect. These results can help wearers choose maximal safe high-heeled shoes to reduce injuries to the bones and lower limbs. |
format | Online Article Text |
id | pubmed-9103558 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91035582022-05-14 Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models Hwang, Yi-Ting Lee, Si-Huei Lin, Bor-Shing Sensors (Basel) Article Women often wear high-heeled shoes for professional or esthetic reasons. However, high-heeled shoes can cause discomfort and injury and can change the body’s center of gravity when maintaining balance. This study developed an assessment system for predicting the maximal safe range for heel height by recording the plantar pressure of participants’ feet by using force-sensing resistor (FSR) sensors and conducting analyses using regression models. Specifically, 100 young healthy women stood on an adjustable platform while physicians estimated the maximal safe height of high-heeled shoes. The collected FSR data combined with and without personal features were analyzed using regression models. The experimental results showed that the regression model based on the pressure data for the right foot had better predictive power than that based on data for the left foot, regardless of the module. The model with two heights had higher predictive power than that with a single height. Furthermore, adding personal features under the condition of two heights afforded the best predictive effect. These results can help wearers choose maximal safe high-heeled shoes to reduce injuries to the bones and lower limbs. MDPI 2022-04-30 /pmc/articles/PMC9103558/ /pubmed/35591131 http://dx.doi.org/10.3390/s22093442 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 | Article Hwang, Yi-Ting Lee, Si-Huei Lin, Bor-Shing Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title | Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title_full | Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title_fullStr | Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title_full_unstemmed | Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title_short | Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and Regression Models |
title_sort | assessment system for predicting maximal safe range for heel height by using force-sensing resistor sensors and regression models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9103558/ https://www.ncbi.nlm.nih.gov/pubmed/35591131 http://dx.doi.org/10.3390/s22093442 |
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