Assessment System for Predicting Maximal Safe Range for Heel Height by Using Force-Sensing Resistor Sensors and
Yi-Ting Hwang1, Si-Huei Lee2,3, Bor-Shing Lin4
1Department of Statistics, National Taipei University, New Taipei City 237303, Taiwan.
Sensors (Basel, Switzerland)
|May 20, 2022
Summary
This study developed a system to predict safe high-heeled shoe heights using plantar pressure data. Incorporating personal features and dual-height data offers the best prediction to prevent lower limb injuries.
Area of Science:
- Biomechanics
- Orthopedics
- Wearable Technology
Background:
- High-heeled shoes are commonly worn for professional and aesthetic reasons.
- They can lead to discomfort, injury, and altered body balance.
- Existing methods for determining safe heel heights are limited.
Purpose of the Study:
- To develop an assessment system for predicting the maximal safe range of high-heeled shoe heights.
- To utilize plantar pressure data and regression modeling for this prediction.
- To reduce injuries associated with wearing high-heeled footwear.
Main Methods:
- Collected plantar pressure data from 100 young healthy women using force-sensing resistor (FSR) sensors.
- Participants stood on an adjustable platform while physicians estimated maximal safe heel height.
- Analyzed FSR data with and without personal features using regression models.
Main Results:
- Regression models based on right foot pressure data showed higher predictive power than the left.
- Models incorporating two height measurements were more predictive than single-height models.
- Including personal features with dual-height data yielded the best predictive effect.
Conclusions:
- The developed system effectively predicts maximal safe high-heeled shoe heights.
- Plantar pressure analysis, especially with personal features and dual-height data, is a viable method.
- This approach can guide wearers in selecting safer footwear, minimizing bone and lower limb injuries.
