Development of a Computer Vision-Based Muscle Stimulation Method for Measuring Muscle Fatigue during Prolonged Low-Load Exposure.

Measuring muscle fatigue is one essential and standard method to quantify the ergonomic risks associated with prolonged low-load exposure. However, measuring muscle fatigue using EMG-based methods has shown conflicting results under low-load but sustained work conditions, e.g., prolonged sitting. Muscle stimulation technology provides an alternative way to estimate muscle fatigue development during such work conditions by monitoring the stimulation-evoked muscle responses, which, however, could be restricted by the accessibility and measurability of targeted muscles. This study proposes a computer vision-based method to overcome such potential restrictions by visually quantifying the muscle belly displacement caused by muscle stimulation. The results demonstrate the ability of the developed computer vision-based stimulation method to detect muscle fatigue from prolonged low-load tasks. Current results can be used as a foundation to develop a sensitive and reliable method to quantify the adverse effects of the daily low-load sustained condition in occupational and nonoccupational settings.