Research on muscle fatigue of upper limb in overhead static work

To explore the muscle fatigue features of upper limb at different heights in overhead static work, an experiment was conducted to obtain the surface electromyography (sEMG) of subjects and their subjective fatigue state based on Borg CR-10 scale. The processing methods of time domain and frequency domain features of sEMG were studied and the multiclass support vector machine (SVM) was used to identify the state of muscle fatigue. By analyzing the muscular contribution, the correlation of subjective ratings and objective muscle fatigue features, ranking order of muscle fatigue accumulation, and muscular fatigue classification and identification, the results show that the muscles contribute above 10% on average are the biceps, deltoid and trapezius, and their cumulative contribution exceeds 70%; and the ranking orders of muscle fatigue accumulation in three heights are H3>H2>H1 for biceps and trapezius and H2>H3>H1 for deltoid; and with the time increase of overhand static operation, the muscle fatigue of upper limb gradually accumulates, resulting in the value of time domain features increases and the frequency domain features decreases, and their changes are consistent; and the accuracy of multiclass SVM is above 90% for identifying muscle fatigue of upper limb in overhead static work.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-10-01
DOI
https://doi.org/10.1051/jnwpu/20244230567/pdf
Primary Topic
Muscle activation and electromyography studies
Type
article
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article

Research on muscle fatigue of upper limb in overhead static work

Springer Link (Chiba Institute of Technology)
Muscle activation and electromyography studies
article

Research on muscle fatigue of upper limb in overhead static work

article en

Abstract

To explore the muscle fatigue features of upper limb at different heights in overhead static work, an experiment was conducted to obtain the surface electromyography (sEMG) of subjects and their subjective fatigue state based on Borg CR-10 scale. The processing methods of time domain and frequency domain features of sEMG were studied and the multiclass support vector machine (SVM) was used to identify the state of muscle fatigue. By analyzing the muscular contribution, the correlation of subjective ratings and objective muscle fatigue features, ranking order of muscle fatigue accumulation, and muscular fatigue classification and identification, the results show that the muscles contribute above 10% on average are the biceps, deltoid and trapezius, and their cumulative contribution exceeds 70%; and the ranking orders of muscle fatigue accumulation in three heights are H3>H2>H1 for biceps and trapezius and H2>H3>H1 for deltoid; and with the time increase of overhand static operation, the muscle fatigue of upper limb gradually accumulates, resulting in the value of time domain features increases and the frequency domain features decreases, and their changes are consistent; and the accuracy of multiclass SVM is above 90% for identifying muscle fatigue of upper limb in overhead static work.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 69%
Muscle activation and electromyography studies
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