Neuromuscular electrical stimulation (NMES) is widely employed for restoring upper limb motor function post-stroke. However, precise control of fine hand movements remains a significant challenge due to the poorly understood time-varying dynamics governing the translation of electrical stimulation into muscle force and joint motion. This study investigated the dynamic modulation of muscle contraction and finger kinematics under varying NMES durations (0.4s, 0.6s, 1s) in 11 healthy subjects. To decouple evoked muscle contractions from joint motion feedback, Ischemic Nerve Block (INB) was employed, after which NMES (0.4s and 1s) was re-administered. Kinematic metrics (angular acceleration and jerk) of evoked finger movements and wavelet spectral features of mechanomyography (MMG) signals were extracted to quantify the time-varying dynamics of NMES-evoked finger movements and/or contraction force dynamics. Results showed that while angular acceleration increased logarithmically with stimulation duration, movement smoothness-quantified by jerk-exhibited a quadratic polynomial decay. Correspondingly, MMG wavelet spectral features (3-20 Hz) exhibited a quadratic polynomial decay as stimulation duration increased, reflecting distinct phases of motor unit recruitment and saturation. A quadratic polynomial correlation (R2 = 0.2574) between jerk and MMG features confirmed that the smoothness of finger motion is directly dictated by the intrinsic mechanical oscillation of muscle fibers. Importantly, these patterns persisted after INB, demonstrating that NMES modulates fine motor output primarily through intrinsic muscle force dynamics rather than sensory feedback loops. These findings provide a physiological basis for optimizing stimulation parameters to achieve smooth, force-regulated control of paralyzed hands.
Zhao et al. (Thu,) studied this question.