Construction Activity Recognition and Ergonomic Risk Assessment Using a Wearable Insole Pressure System
Publication: Journal of Construction Engineering and Management
Volume 146, Issue 7
Abstract
Overexertion-related construction activities are identified as a leading cause of work-related musculoskeletal disorders (WMSDs) among construction workers. However, few studies have focused on the automated recognition of overexertion-related construction workers’ activities as well as assessing ergonomic risk levels, which may help to minimize WMSDs. Therefore, this study examined the feasibility of using acceleration and foot plantar pressure distribution data captured by a wearable insole pressure system for automated recognition of overexertion-related construction workers’ activities and for assessing ergonomic risk levels. The proposed approach was tested by simulating overexertion-related construction activities in a laboratory setting. The classification accuracy of five types of supervised machine learning classifiers was evaluated with different window sizes to investigate classification performance and further estimate physical intensity, activity duration, and frequency information. Cross-validation results showed that the Random Forest classifier with a 2.56-s window size achieved the best classification accuracy of 98.3% and a sensitivity of more than 95.8% for each category of activities using the best features of combined data set. Furthermore, the estimation of corresponding ergonomic risk levels was within the same level of risk. The findings may help to develop a noninvasive wearable insole pressure system for the continuous monitoring and automated activity recognition, which could assist researchers and safety managers in identifying and assessing overexertion-related construction activities for minimizing the development of WMSDs’ risks among construction workers.
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Data Availability Statement
All raw data and feature extraction codes generated or analyzed during the study are available from the corresponding author by request.
Acknowledgments
The authors acknowledged the support from the Department of Building and Real Estate of The Hong Kong Polytechnic University, the General Research Fund (GRF) Grant (BRE/PolyU 152099/18E) entitled “Proactive Monitoring of Work-Related MSD Risk Factors and Fall Risks of Construction Workers Using Wearable Insoles.” Special thanks are given to Mr. Mark Ansah Kyeredey for assisting the experimental set-up and the participants involved in this study.
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Published In
Journal of Construction Engineering and Management
Volume 146 • Issue 7 • July 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: May 29, 2019
Accepted: Dec 23, 2019
Published online: May 6, 2020
Published in print: Jul 1, 2020
Discussion open until: Oct 6, 2020
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