Abstract
Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity () and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity.
Highlights
Good locomotor function is essential for survival in the majority of animals and depends on appropriate functioning of the neuromusculoskeletal system
The theoretical analysis completed here predicts that structure in physiological myoelectric signals from individual muscles, represented by EnHL, persists over time periods of up to 40.00 ms
The predicted EnHLs were influenced by the ratio of standard deviation and mean signal intensity, and mainly reflected interplay between myoelectric activation duration and duty cycle, despite the signals having been filtered to remove stride/cycle frequency components
Summary
Good locomotor function is essential for survival in the majority of animals and depends on appropriate functioning of the neuromusculoskeletal system. The majority of scientific work investigating neuromuscular function has focused on studying steady-state, isometric contractions, and as such underlying principles that govern appropriate neuromuscular responses to tasks of different complexity and intensity are difficult to establish. Motor unit activity can be detected from changes in muscle fiber membrane potential, triggered by the arrival of impulses from the central nervous system, and recorded using electromyography. The resulting myoelectric signal is the interference pattern produced by superposition of motor unit action potentials within the detection volume of a recording electrode, and can be considered to represent the command signals sent from the central nervous system
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