EEG-Based Spectral Analysis ShowingBrainwave Changes Related to ModulatingProgressive Fatigue During a ProlongedIntermittent Motor Task

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue manifested by its reduced capacity to generate force or power. Fatigue resulted from voluntary muscle contractions comprises a central and peripheral component, which demands a gradually increasing effort to perform the task as time elapses. However, we still lack a complete understanding of brain contribution to the enhancement of effort to cope with progressing fatigue because of repeated submaximal muscle contractions. The knowledge of how muscle fatigue modulates brain activities in a healthy population will help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks. The intermittent motor tasks closely resemble many activities of daily living (ADL), thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects performing intermittent submaximal muscle contractions until self-perceived exhaustion. Fourteen participants (median age 51.5 years; age range 26-72 years; 5 males) repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted ~5 s with a 2-s rest between trials. The force, EEG, and surface EMG (from elbow joint muscles) data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency (TF) characteristics across the conditions. The TF analyses were conducted both at the channel and source level. The outcome of the channel- and source-level analyses reveal that the theta, alpha, and beta power spectral densities (PSDs) vary in proportion to fatigue levels in cortical motor areas. Importantly, the pairwise PSD differences between the fatigue conditions survived the statistical inferential tests with a p-value threshold of 0.05. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post- contraction EEG data. The findings would enhance our understanding of the etiology and physiology of voluntary motor action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies and develop therapeutic strategies for restoring the patients' ability to participate in ADL by mitigating central and muscle fatigue.