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.
Highlights
Musculoskeletal disorders (MSDs) caused by manual lifting tasks have been perceived for quite some time as one of the primary work-related injuries which influences the personal satisfaction of industrial workers around the world [1, 2]
Even though intramuscular EMG provides additional benefits to overcome the drawbacks of surface EMG such as maintaining robust electrode contact with the skin and the capacity to record from profound muscles with little EMG crosstalk [27], sEMG and imEMG have been proven to have equal classification performance for data of comparative nature
The results show that this new fatigue index quantifies the EMG signal elongation during a contraction and makes it a suitable fatigue index
Summary
Musculoskeletal disorders (MSDs) caused by manual lifting tasks have been perceived for quite some time as one of the primary work-related injuries which influences the personal satisfaction of industrial workers around the world [1, 2]. Common reasons of MSDs in manual lifting are due to improper lifting and muscle fatigue. National Institute of Occupational Safety and Health (NIOSH) has published a technical report entitled Work Practices Guide for Manual Lifting as a reference to perform correct lifting [3]. In terms of muscle fatigue monitoring, researchers are still in search of finding the best processing technique to assess the human muscle condition
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