TY - GEN
T1 - Estimation of Lifting and Carrying Load During Manual Material Handling
AU - Trkov, Mitja
AU - Merryweather, Andrew S.
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Low back injuries and low back pain are often caused by improper task execution, overuse or lack of guidance and training. Our current understanding of dose-response relationships between risk factors that contribute to these injuries remains unclear. Enhanced monitoring of risk factors contributing to injuries could provide more complete exposure-response information. It is difficult to continuously monitor workers and their exposures to ergonomic risk factors using existing technologies. This paper presents a practical approach to advance continuous measurements of common risk factors by quantifying the weight of an object during lifting and carrying, lift frequency and lift duration during manual material handling (MMH). We estimate these parameters based on the ground reaction forces (GRF) and considering trunk dynamics. The results show that by considering trunk dynamics and applying simple signal processing techniques, we can precisely estimate these risk parameters. These parameters can then be used to estimate injury risk of workers. The developed methodology is designed for real-time continuous monitoring applications and sets the foundation for future development of in-field monitoring of workers with wearable sensors.
AB - Low back injuries and low back pain are often caused by improper task execution, overuse or lack of guidance and training. Our current understanding of dose-response relationships between risk factors that contribute to these injuries remains unclear. Enhanced monitoring of risk factors contributing to injuries could provide more complete exposure-response information. It is difficult to continuously monitor workers and their exposures to ergonomic risk factors using existing technologies. This paper presents a practical approach to advance continuous measurements of common risk factors by quantifying the weight of an object during lifting and carrying, lift frequency and lift duration during manual material handling (MMH). We estimate these parameters based on the ground reaction forces (GRF) and considering trunk dynamics. The results show that by considering trunk dynamics and applying simple signal processing techniques, we can precisely estimate these risk parameters. These parameters can then be used to estimate injury risk of workers. The developed methodology is designed for real-time continuous monitoring applications and sets the foundation for future development of in-field monitoring of workers with wearable sensors.
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U2 - 10.1007/978-3-319-96068-5_17
DO - 10.1007/978-3-319-96068-5_17
M3 - Conference contribution
AN - SCOPUS:85052154687
SN - 9783319960678
T3 - Advances in Intelligent Systems and Computing
SP - 153
EP - 161
BT - Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume VIII
A2 - Bagnara, Sebastiano
A2 - Fujita, Yushi
A2 - Tartaglia, Riccardo
A2 - Albolino, Sara
A2 - Alexander, Thomas
PB - Springer Verlag
T2 - 20th Congress of the International Ergonomics Association, IEA 2018
Y2 - 26 August 2018 through 30 August 2018
ER -