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Review
. 2017:2017:3937254.
doi: 10.1155/2017/3937254. Epub 2017 Feb 19.

EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

E F Shair  1 , S A Ahmad  2 , M H Marhaban  2 , S B Mohd Tamrin  3 , A R Abdullah  4
Affiliations
Review

EMG Processing Based Measures of Fatigue Assessment during Manual Lifting

E F Shair et al. Biomed Res Int. 2017.

Abstract

Manual lifting is one of the common practices used in the industries to transport or move objects to a desired place. Nowadays, even though mechanized equipment is widely available, manual lifting is still considered as an essential way to perform material handling task. Improper lifting strategies may contribute to musculoskeletal disorders (MSDs), where overexertion contributes as the highest factor. To overcome this problem, electromyography (EMG) signal is used to monitor the workers' muscle condition and to find maximum lifting load, lifting height and number of repetitions that the workers are able to handle before experiencing fatigue to avoid overexertion. Past researchers have introduced several EMG processing techniques and different EMG features that represent fatigue indices in time, frequency, and time-frequency domain. The impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper. It is believed that this paper will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications.

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Conflict of interest statement

The authors declare that there is no conflict of interests regarding the publication of this paper.

Figures

Figure 1
Figure 1
Overall view of the electromyography signal processing methods that are reviewed in this manuscript.
See this image and copyright information in PMC

References

    1. Gallagher S., Heberger J. R. Examining the interaction of force and repetition on musculoskeletal disorder risk: a systematic literature review. Human Factors. 2013;55(1):108–124. doi: 10.1177/0018720812449648. - DOI - PMC - PubMed
    1. Eatough E. M., Way J. D., Chang C.-H. Understanding the link between psychosocial work stressors and work-related musculoskeletal complaints. Applied Ergonomics. 2012;43(3):554–563. doi: 10.1016/j.apergo.2011.08.009. - DOI - PubMed
    1. Waters T. R., Putz-Anderson V., Garg A., Fine L. J. Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics. 1993;36(7):749–776. doi: 10.1080/00140139308967940. - DOI - PubMed
    1. Roquelaure Y., Ha C., Leclerc A., et al. Epidemiologic surveillance of upper-extremity musculoskeletal disorders in the working population. Arthritis Care and Research. 2006;55(5):765–778. doi: 10.1002/art.22222. - DOI - PubMed
    1. Arif H., Kosnan M. S. E., Jusoff K., et al. Finite element analysis of conceptual lumbar spine for different lifting position. World Applied Sciences Journal. 2013;21:68–75. doi: 10.5829/idosi.wasj.2013.21.1009. - DOI