TY - GEN
T1 - Postural Balance of Kneeling Gaits on Inclined and Elevated Surface for Construction Workers
AU - Chen, Siyu
AU - Yu, Yi
AU - Di, Chong
AU - Stevenson, Duncan T.
AU - Trkov, Mitja
AU - Gong, Jie
AU - Yi, Jingang
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/23
Y1 - 2021/8/23
N2 - We present a human postural balance study on quiet stance and kneeling gaits on inclined and high elevated surfaces for construction workers. To simulate the high elevation, an immersive mixed reality environment is built with an actual inclined roof surface to create somatosensory haptic feedback. We quantify the postural balance during quiet kneeling and stance through measurements of the center of pressure and sway motion of the upper-body under various inclined angles and heights. The results of center of pressure and trunk acceleration measurements show smaller postural sway during kneeling compared to standing. A mathematical model is also presented to help understand the experimental results and potentially provide design guidance for further intervention to prevent and mitigate the fall risk for construction workers. The model and controller parameters are optimized to precisely capture and explain the experimental results.
AB - We present a human postural balance study on quiet stance and kneeling gaits on inclined and high elevated surfaces for construction workers. To simulate the high elevation, an immersive mixed reality environment is built with an actual inclined roof surface to create somatosensory haptic feedback. We quantify the postural balance during quiet kneeling and stance through measurements of the center of pressure and sway motion of the upper-body under various inclined angles and heights. The results of center of pressure and trunk acceleration measurements show smaller postural sway during kneeling compared to standing. A mathematical model is also presented to help understand the experimental results and potentially provide design guidance for further intervention to prevent and mitigate the fall risk for construction workers. The model and controller parameters are optimized to precisely capture and explain the experimental results.
UR - http://www.scopus.com/inward/record.url?scp=85117010724&partnerID=8YFLogxK
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U2 - 10.1109/CASE49439.2021.9551444
DO - 10.1109/CASE49439.2021.9551444
M3 - Conference contribution
AN - SCOPUS:85117010724
T3 - IEEE International Conference on Automation Science and Engineering
SP - 1934
EP - 1939
BT - 2021 IEEE 17th International Conference on Automation Science and Engineering, CASE 2021
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Automation Science and Engineering, CASE 2021
Y2 - 23 August 2021 through 27 August 2021
ER -