ArticleSensors (Basel, Switzerland)2022
Customized Textile Capacitive Insole Sensor for Center of Pressure Analysis.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The trial behind it
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Who cites it
4 citing papers in PubMed.
- Technical Characteristics and Biomedical Applications of Flexible Pressure Sensor Matrices: A Scoping Review.Sensors (Basel, Switzerland) · 2026Article
- Application of artificial muscle e-rubber for healthcare sensing: verification of measurement properties as a smart insole.Frontiers in bioengineering and biotechnology · 2025Article
- Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey.Sensors (Basel, Switzerland) · 2024Review
- Dynamic Characterization of a Low-Cost Fully and Continuously 3D Printed Capacitive Pressure-Sensing System for Plantar Pressure Measurements.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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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Registered trials
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