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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.
Afiliação
  • Hwang YT; Department of Statistics, National Taipei University, New Taipei City 237303, Taiwan.
  • Lee SH; Department of Physical Medicine and Rehabilitation, Taipei Veterans General Hospital, Taipei 112, Taiwan.
  • Lin BS; Faculty of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan.
Sensors (Basel) ; 22(9)2022 Apr 30.
Article em En | MEDLINE | ID: mdl-35591131
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Calcanhar / Caminhada Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Calcanhar / Caminhada Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article