Characterization of motor unit activities during isometric elbow flexion with different speeds

The neural mechanisms regulating muscle activity exhibit variations under different contraction levels and speeds. This study aims to systematically characterize motor unit (MU) behavior during isometric elbow flexion tasks performed at different force levels and contraction speeds, using high-density surface electromyography (HDsEMG) decomposition.

HDsEMG signals were recorded from the biceps and triceps brachii muscles of 61 participants during force-tracking tasks at four force levels (10%, 30%, 50%, and 70% of maximum voluntary contraction, MVC) and three contraction speeds (5%, 10%, and 20%MVC/s). A convolution kernel compensation algorithm was used to decompose the sEMG signals into MU spike trains. Motor unit features were extracted and analyzed, including recruitment thresholds, discharge rates, action potential amplitude, common drive measures, and force-tracking performance.

Across varying contraction levels and speeds, the number of identified MUs from each condition ranged from 9 to 15 for the biceps brachii and 3 to 9 MUs for triceps brachii. Motor unit recruitment and action potential amplitudes increased with force, consistent with the size principle. Faster contractions led to higher discharge rates at recruitment and derecruitment, greater common drive (as indicated by principal component analysis), and higher force-tracking error. These adaptations are more pronounced in the biceps brachii, which was the primary muscle involved in the contraction.

Motor unit behavior is modulated by contraction force and speed, with faster contractions eliciting higher discharge rates and common drive. These findings underscore the neuromechanical adaptability of the motor unit system and have implications for motor function assessment, rehabilitation, and the development of myoelectric interfaces.