Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Industrial and Managements Systems Engineering

Committee Chair

Ashish D Nimbarte

Committee Co-Chair

Robert C Creese

Committee Member

Majid Jaridi

Committee Member

Ashish D. Nimbarte.


Objective assessment of neuromuscular fatigue caused by sub-maximal repetitive exertions is essential for the early detection and prevention of risks of neck and shoulder musculoskeletal disorders. In recent years, discrete wavelet transforms (DWT) of surface electromyography (SEMG) has been used to evaluate muscle fatigue, especially during dynamic contractions when the SEMG signal is non-stationary. However, its application to neck muscle fatigue assessment is not well established. Therefore, the purpose of this study was to establish DWT analysis as a suitable method to conduct quantitative assessment of neck muscle fatigue caused by dynamic exertions. Ten human participants performed 40 minutes of fatiguing repetitive arm and neck exertions. SEMG data from the upper trapezius and sternocleidomastoid muscles were recorded. Ten most commonly used orthogonal wavelet functions were used to conduct DWT analysis. A significant increase in the power was observed at lower frequency bands of 6-12Hz, 12-23 Hz, and 23-46 Hz with the onset and development of fatigue for most of the wavelet functions. Among ten wavelet function, a relatively higher power estimation, consistent statistical trend and better power contrast with the onset and development of fatigue was observed for the Rbio3.1 wavelet function. The results of this study will assist Professional Ergonomists to automate the process of localized muscle fatigue estimation, which could have applications related to improving working environment.