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Customized Textile Capacitive Insole Sensor for Center of Pressure Analysis
Jong-Gab Ho1, Young Kim1, Se-Dong Min1,2
1Department of Software Convergence, Soonchunhyang University, Asan 31538, Republic of Korea.
Sensors (Basel, Switzerland)
|December 11, 2022
Summary
Researchers developed a cost-effective insole sensor (I-TCPs) to measure plantar pressure and center of pressure during walking. The I-TCPs demonstrated good accuracy compared to existing systems, showing potential for wearable health technology.
Area of Science:
- Biomechanics
- Wearable Technology
- Sensor Development
Background:
- Center of pressure (COP) is a key metric in human locomotion analysis.
- Accurate measurement of plantar pressure (PP) and COP trajectory is crucial for understanding gait.
- Existing systems for PP and COP measurement can be expensive and cumbersome.
Purpose of the Study:
- To develop and validate a cost-effective, lightweight insole-type textile capacitive sensor (I-TCPs).
- To analyze plantar pressure distribution and center of pressure trajectory using the developed I-TCPs.
- To compare the accuracy of I-TCPs against a gold-standard system (F-scan).
Main Methods:
- Development of insole-type textile capacitive sensors (I-TCPs).
- Static baseline tests and dynamic gait experiments at self-selected comfortable and fast speeds.
- Comparison of I-TCPs pressure data with F-scan measurements.
Main Results:
- I-TCPs successfully recognized plantar pressure segments at different gait speeds.
- In comfortable gait speed, average RMSE was 1.29 ± 0.47 mm for COPx and 12.55 ± 5.08 mm for COPy.
- COP correlation with F-scan was 0.54 ± 0.09 for COPx and 0.92 ± 0.04 for COPy, with COPy showing stronger correlation.
Conclusions:
- The developed I-TCPs offer a viable, cost-effective solution for analyzing plantar pressure and center of pressure.
- The sensor demonstrates good accuracy and correlation with existing systems, suitable for various gait speeds.
- Findings support future applications in rehabilitation engineering, ICT devices, and smart wearable sensors.

