Ground Reaction Force Analysis of Robot-Assisted Walking Using Inertial Sensors
Issued Date
2025-01-01
Resource Type
Scopus ID
2-s2.0-105037426861
Journal Title
2025 International Convention on Rehabilitation Engineering and Assistive Technology I Create 2025 Conference Proceedings
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SCOPUS
Bibliographic Citation
2025 International Convention on Rehabilitation Engineering and Assistive Technology I Create 2025 Conference Proceedings (2025)
Suggested Citation
Moonjaita C., Sivaraman D., Sai-Aroon K., Luangon P., Pillai B.M., Suthakorn J. Ground Reaction Force Analysis of Robot-Assisted Walking Using Inertial Sensors. 2025 International Convention on Rehabilitation Engineering and Assistive Technology I Create 2025 Conference Proceedings (2025). doi:10.1109/I-CREATE67590.2025.11478153 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/116578
Title
Ground Reaction Force Analysis of Robot-Assisted Walking Using Inertial Sensors
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Abstract
The growing elderly population faces increasing mobility challenges, particularly knee joint problems during walking, which limit independence and increase the risk of falls. Traditional force plate measurements for ground reaction force (GRF) analysis are constrained to laboratory environments, limiting the assessment of assistive technologies in natural settings. This study developed a mathematical framework to estimate the GRF during robot-assisted walking using inertial sensors, with the BART LAB AI-Elderly Supporting Robot designed specifically for elderly mobility assistance. Ten healthy participants performed walking trials under controlled and robot-assisted conditions to validate the proposed measurement framework. Inertial measurement unit sensors captured motion data, and mathematical models estimated the GRF by incorporating gravitational, dynamic, and robotic assistance components. Robotic assistance achieved a 28.9 ± 8.6% peak GRF reduction, with 90% of the participants showing clinically meaningful improvements (>20%). Individual reductions ranged from 12.4-39.8%, equivalent to a substantial joint load reduction. The framework successfully quantifies the effectiveness of robotic assistance without force plate constraints, providing a foundation for the objective evaluation of elderly mobility support systems before clinical implementation.