A methodological framework for assessing neural control of shoulder muscles during multi-directional isometric tasks using high-density surface electromyography

The complex movements of the shoulder rely on the coordinated activation of large muscles including the deltoid, pectoralis major, trapezius and latissimus dorsi. However, detailed knowledge of their neuromuscular control remains limited. This study aimed to develop a methodological framework to investigate the neural control of shoulder muscles by combining a 6-degree-of-freedom load cell attached to an industrial robotic arm with high-density surface electromyograms (HDsEMG). Six healthy participants performed isometric contractions (abduction, adduction, flexion and extension) at 30% of maximal voluntary contraction with the shoulder positioned at 30° and 65° of lateral abduction. HDsEMGs were recorded from the four muscles and analysed at both the global activation and motor unit levels. Global activation was quantified using root-mean-square (RMS) amplitude and topographic maps. Moreover, HDsEMGs were decomposed into individual motor unit spike trains and motor unit behaviour was characterized by mean discharge rate, coefficient of variation of inter-spike interval, and spatial distribution of motor unit action potentials (MUAPs). RMS maps revealed movement-specific activation within and between muscles, with the deltoid and trapezius active across all tasks, while the pectoralis and latissimus dorsi were predominantly activated during flexion and extension. Motor unit discharge rates also showed task-dependent recruitment. MUAP spatial distributions further showed distinct motor unit territories within arrays, suggesting region-specific recruitment strategies across movements. In conclusion, this framework demonstrates that individual motor unit activity can be reliably measured non-invasively in the main superficial shoulder muscles. The approach provides a methodological basis for incorporating neural control into biomechanical models of shoulder function.