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Influence of Select Modes of Load Carriage on Movement Biomechanics of Industrial Workers

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Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) (IEA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 819))

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Abstract

A study was conducted with an aim to determine the changes of human lower limb biomechanics biomechanics while carrying loads in selective modes among industrial workers of India and to suggest the biomechanically efficient mode of load carriage. Industrial workers (n = 20) in the age range of 22 to 58 years were selected and asked to carry loads on head, across one shoulder and in hands. Qualisys Motion Capture System (Sweden), Kistler Force Plate (Switzerland) and Polar S810i HR monitor, Finland were used to record data. Heart rate was recorded at rest and during select modes of load carriage with 40% of individual body weight i.e. loads on head, shoulder and hand. Walking speed for head load, shoulder load and hand load were 4.19 ± 0.55 km.hr−1, 4.09 ± 0.82 km.hr−1 and 3.94 ± 0.84 km.hr−1 respectively. Double limb support time while carrying loads has been found lowest in case of head mode (0.65 ± 0.46 s) followed by hand mode (0.67 ± 0.14 s) and shoulder mode (0.68 ± 0.06 s) of load carriage. There is a gradual increase in hip flexon from head to shoulder and hand load condition and gradual decrease in ground reaction force from head to shoulder and hand load conditions. Considering the changes in the physiological parameters along with the biomechanical parameters, head load was found to be more productive in comparison to shoulder and hand load modes. Results demonstrated a significant changes in kinetic and kinematic parameters of workers at selective load conditions. Findings would provide substantial input for designing work and work rest cycle for different industrial manual workforce.

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Correspondence to Rauf Iqbal .

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Iqbal, R., Thakurta, A.G. (2019). Influence of Select Modes of Load Carriage on Movement Biomechanics of Industrial Workers. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-319-96089-0_63

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