Muscle Fatigue Analysis During Welding Tasks Using sEMG and Recurrence Quantification Analysis

The main goal of this study was to detect muscle fatigue and to identify muscles vulnerable to musculoskeletal disorders by evaluating muscle activation of subjects during welding tasks. In this study, six subjects performed two different welding tasks for a total of three hours. Surface electromyography (sEMG) was used to record the muscle activation of sixteen different muscles. Recurrence Quantification Analysis (RQA) was then used to analyze the EMG data. In addition, a subjective fatigue assessment was conducted to draw comparisons with the RQA results. According to the RQA results, twelve of the tested muscles experienced fatigue by showing significant difference in RQA values (p-value < 0.05) between the first and last 10 minutes of the experiment. Moreover, time-to-fatigue results obtained from RQA and subjective analysis were closely correlated for seven muscle groups. This study showed that RQA can be used in ergonomic studies for evaluating muscle activation during construction tasks.

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Prediction of Muscle Fatigue during Minimally Invasive Surgery Using Recurrence Quantification Analysis

Minimally Invasive Surgery ◽

10.1155/2016/5624630 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Ali Keshavarz Panahi ◽

Sohyung Cho

Keyword(s):

Minimally Invasive Surgery ◽

Minimally Invasive ◽

Muscle Fatigue ◽

Invasive Surgery ◽

Muscle Activation ◽

Recurrence Quantification Analysis ◽

Recurrence Quantification ◽

Quantification Analysis ◽

Muscle Groups ◽

Muscle Activations

Due to its inherent complexity such as limited work volume and degree of freedom, minimally invasive surgery (MIS) is ergonomically challenging to surgeons compared to traditional open surgery. Specifically, MIS can expose performing surgeons to excessive ergonomic risks including muscle fatigue that may lead to critical errors in surgical procedures. Therefore, detecting the vulnerable muscles and time-to-fatigue during MIS is of great importance in order to prevent these errors. The main goal of this study is to propose and test a novel measure that can be efficiently used to detect muscle fatigue. In this study, surface electromyography was used to record muscle activations of five subjects while they performed fifteen various laparoscopic operations. The muscle activation data was then reconstructed using recurrence quantification analysis (RQA) to detect possible signs of muscle fatigue on eight muscle groups (bicep, triceps, deltoid, and trapezius). The results showed that RQA detects the fatigue sign on bilateral trapezius at 47.5 minutes (average) and bilateral deltoid at 57.5 minutes after the start of operations. No sign of fatigue was detected for bicep and triceps muscles of any subject. According to the results, the proposed novel measure can be efficiently used to detect muscle fatigue and eventually improve the quality of MIS procedures with reducing errors that may result from overlooked muscle fatigue.

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