| Summary: | To stimulate neuroplasticity, the stroke patient often receives repetitive and high load robotic rehabilitation therapy. Given their impaired motor function, the patients are prone to muscle fatigue. Muscle fatigue lead patients to compensate for upper limb motion by recruiting trunk and shoulder motions, resulting in undesirable rehabilitation motion and a subsequent risk of injury. However, fatigue compensation is not detected during upper-limb robotic rehabilitation training in the existing rehabilitation robot. The aim of this study was to detect the compensation caused by fatigue based on surface electromyography (sEMG). Eight healthy subjects performed three basic repetitive resistance rehabilitation training tasks, to elicit three types of common stroke fatigue compensatory synergies. The subjective fatigue score and sEMGs of the main muscles used were acquired to determine the fatigue state. The compensatory motion was recorded by a motion capture apparatus. The sEMG median frequency (MDF) of the main muscles used and the overall fatigue compensation were calculated. With the development of fatigue, the subjects exhibited more signs of fatigue compensation. The motion types slightly increased the degree of corresponding basic compensation. However, the subjects exhibited similar ranges and trends in the overall compensation. A strong correlation was found between sEMG MDF and overall fatigue compensation. Thus, fatigue compensation can be detected based on the body's status regardless of the type of motion. The sEMG-based detection of fatigue compensation proposed in this study is a reliable way to detect fatigue compensation and improve the quality of therapeutic exercise during upper-limb robotic rehabilitation training.
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