Abstract
Continuous force output containing numerous intermittent force pulses is not completely smooth. By characterizing force fluctuation properties and force pulse metrics, this study investigated adaptive changes in trajectory control, both force-generating capacity and force fluctuations, as fatigue progresses. Sixteen healthy subjects (20–24 years old) completed rhythmic isometric gripping with the non-dominant hand to volitional failure. Before and immediately following the fatigue intervention, we measured the gripping force to couple a 0.5 Hz sinusoidal target in the range of 50–100% maximal voluntary contraction. Dynamic force output was off-line decomposed into 1) an ideal force trajectory spectrally identical to the target rate; and 2) a force pulse trace pertaining to force fluctuations and error-correction attempts. The amplitude of ideal force trajectory regarding to force-generating capacity was more suppressed than that of the force pulse trace with increasing fatigue, which also shifted the force pulse trace to lower frequency bands. Multi-scale entropy analysis revealed that the complexity of the force pulse trace at high time scales increased with fatigue, contrary to the decrease in complexity of the force pulse trace at low time scales. Statistical properties of individual force pulses in the spatial and temporal domains varied with muscular fatigue, concurrent with marked suppression of gamma muscular oscillations (40–60 Hz) in the post-fatigue test. In conclusion, this study first reveals that muscular fatigue impairs the amplitude modulation of force pattern generation more than it affects the amplitude responsiveness of fine-tuning a force trajectory. Besides, motor fatigue results disadvantageously in enhancement of motor noises, simplification of short-term force-tuning strategy, and slow responsiveness to force errors, pertaining to dimensional changes in force fluctuations, scaling properties of force pulse, and muscular oscillation.
Highlights
When muscles are exhausted, they cannot generate enough force to achieve a target level because of a reduction in forcegenerating capacity
Muscular fatigue typically manifests as variations in the amplitude and spectrum of surface electromyograms (EMG); myoelectrical manifestations of a fatigued muscle vary with the load characteristics of a fatigue protocol [1,2], such as static versus dynamic contractions [3] and maximal versus submaximal contractions [4,5]
Force tracking with visual feedback results in better tracking congruency, smaller force fluctuations, and greater complexity of force fluctuations than force tracking without visual feedback [13,14]
Summary
They cannot generate enough force to achieve a target level because of a reduction in forcegenerating capacity. An invariant measure of change in an exhausted contraction appears to be increases in the size of force fluctuations [6,7], traditionally viewed as enhancement of background noises in motor drive [8,9]. A larger size of force fluctuations with fatigue progress may impair task quality, how time-dependent structure of force fluctuations varies with fatigue is little understood. For an un-fatigued muscle, the size and the complexity of force fluctuations are influenced by separate control processes [10,11]. Increases in the complexity of force fluctuations do not necessarily undermine task quality, but they do reflect the engagement of error corrections. In aged adults, force fluctuations are greater in size but less complex for constant-force level tasks [15]
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