Journal
SENSORS
Volume 22, Issue 23, Pages -Publisher
MDPI
DOI: 10.3390/s22239390
Keywords
gait; insole; textile capacitive pressure sensor; wearable sensor; center of pressure
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2021R1I1A3059769]
- Soonchunhyang University Research Fund
- BK21 FOUR (Fostering Outstanding Universities for Research) [5199990914048]
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In this study, a lightweight insole-type textile capacitive sensor was developed to analyze plantar pressure distribution and center of pressure trajectory. The results showed that the sensor was capable of accurately identifying pressure segments at different gait speeds, and it exhibited similar accuracy and consistency compared to the traditional F-scan sensor. These findings provide a basis for future research in rehabilitation engineering and the development of smart devices.
Center of pressure refers to the centroid of the ground reaction force vector detected underneath the walking foot, which is a summary measure representing body segment movements during human locomotion. In this study, we developed a cost-effective, lightweight insole-type textile capacitive sensor (I-TCPs) to analyze plantar pressure (PP) distribution and center of pressure (COP) trajectory. To test the accuracy of I-TCPs, the measured pressure data was compared with that of F-scan. The sensor performance test was divided into a static baseline test and a dynamic gait experiment, both at two different gait speeds self-selected by the subjects. Static gait results showed that I-TCPs were capable of recognizing PP segments at different gait speeds. Dynamic gait results showed an average RMSE of 1.29 +/- 0.47 mm in COPx (mediolateral shift) and 12.55 +/- 5.08 mm in COPy (anteroposterior shift) at a comfortable gait speed. The COP correlation between I-TCPs and F-scan was 0.54 +/- 0.09 in COPx and 0.92 +/- 0.04 in COPy in comfortable gait speed conditions, in which COPy values presented a stronger correlation. RMSE and correlation in fast gait speed conditions also showed similar results. The findings of this study can be the basis for future research, including rehabilitation engineering, developing ICT devices, and creating smart wearable sensors to improve quality of life for patients and healthy individuals.
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