Bidirectional Delay Estimation of Motor Control Systems at Different Muscle Contraction Levels.

Reliable estimation of bidirectional delays in motor control systems is crucial for uncovering underlying physiological mechanisms. However, previous studies have largely overlooked the delay in information transmission from the perspective of movement levels, limiting the understanding of physiological delays. This study aims to investigate the conduction delay between the brain and muscles, and uncover the underlying physiological mechanisms of hand motor function through delay estimation. Based on the analogous cumulant density method, the delay between the brain cortex and hand muscles was evaluated at different levels of force contraction. We found that there was no significant difference in delay observed at different levels of force, regardless of whether the analysis was based on the raw electromyography (EMG) or EMG signals synthesized from motor unit (MU). In the descending pathway from the brain to the muscles, it was observed that the positive delay was significantly shorter at low force levels compared to moderate force levels. Moreover, by utilizing the features of the minimum spanning tree (MST) graph to characterize changes in the brain functional network at different levels of movement, it was found that in the beta frequency band, both the diameter and radius descriptors of the MST graph were significantly larger during low and high force movements compared to moderate force movement. This study suggests a potential correlation between physiological delays and muscle performance. Sustaining balance during low-force movements requires the integration of more resources, resulting in lower information transmission efficiency. Conversely, in the motor control loop, information is transmitted more quickly from the central nervous system to peripheral muscle tissues during low-force contraction.