Fall risk assessment of construction workers based on biomechanical gait stability parameters using wearable insole pressure system

Author:

Antwi-Afari Maxwell Fordjour,Li Heng

Funder

Department of Building and Real Estate of The Hong Kong Polytechnic University

General Research Fund

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems

Reference69 articles.

1. Smartphone-based construction workers' activity recognition and classification;Akhavian;Autom. Constr.,2016

2. Identification of potential biomechanical risk factors for low back disorders during repetitive rebar lifting;Antwi-Afari;Constr. Innovation: Inf. Process Manage.,2018

3. M.F. Antwi-Afari, Y. Yu, H. Li, A. Darko, J. Seo, A.Y.L. Wong, Automated detection and classification of construction workers’ awkward working postures using wearable insole pressure sensors, in: Proceedings of 1st Postgraduate in Applied Research Conference in Africa (ARCA), Accra, Ghana, February 20–24, 2018.

4. M.F. Antwi-Afari, H. Li, J. Seo, S. Lee, D.J. Edwards, A.Y.L. Wong, Wearable insole pressure sensors for automated detection and classification of slip-trip-loss-of-balance events in construction worker, in: Proceedings of Construction Research Congress, New Orleans, Louisiana, USA, April 2–4, 2018. https://doi.org/10.1061/9780784481288.008.

5. Effects of different weight and lifting postures on postural control during repetitive lifting tasks;Antwi-Afari;Int. J. Build. Pathol. Adaptation,2017

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