Abstract
Objective. We present a non-invasive framework for investigating efferent commands to 14 extrinsic and intrinsic hand muscles. We extend previous studies (limited to a few muscles) on common synaptic input among pools of motor neurons in a large number of muscles. Approach. Seven subjects performed sinusoidal isometric contractions to complete seven types of grasps, with each finger and with three combinations of fingers in opposition with the thumb. High-density surface EMG (HD-sEMG) signals (384 channels in total) recorded from the 14 muscles were decomposed into the constituent motor unit action potentials. This provided a non-invasive framework for the investigation of motor neuron discharge patterns, muscle coordination and efferent commands of the hand muscles during grasping. Moreover, during grasping tasks, it was possible to identify common neural information among pools of motor neurons innervating the investigated muscles. For this purpose, principal component analysis (PCA) was applied to the smoothed discharge rates of the decoded motor units. Main results. We found that the first principal component (PC1) of the ensemble of decoded motor neuron spike trains explained a variance of (53.0 ± 10.9) % and was positively correlated with force (R = 0.67 ± 0.10 across all subjects and tasks). By grouping the pools of motor neurons from extrinsic or intrinsic muscles, the PC1 explained a proportion of variance of (57.1 ± 11.3) % and (56.9 ± 11.8) %, respectively, and was correlated with force with R = 0.63 ± 0.13 and 0.63 ± 0.13, respectively. Significance. These observations demonstrate a low dimensional control of motor neurons across multiple muscles that can be exploited for extracting control signals in neural interfacing. The proposed framework was designed for hand rehabilitation perspectives, such as post-stroke rehabilitation and hand-exoskeleton control.
Highlights
The human hand is a neuromuscular-skeletal system fundamental for interacting with the external environment and for communicating
We propose for the first time a non-invasive framework for the investigation of motor neuron discharge patterns, muscle coordination and efferent commands to extrinsic and intrinsic hand muscles for a total of 14 muscle compartments. By applying this framework to seven grasp types, we demonstrate that it enables to discriminate the location of the electrical activity of single motor units among the investigated muscles and to determine common neural information among pools of motor units of the main intrinsic and extrinsic muscles actuating the hand
The number of motor units identified per grid was 6.4 ± 3.4, mean firing rate (MFR) was 14.4 ± 8.8 Hz, and pulse-to-noise ratio (PNR) was 30.4 ± 4.8 dB
Summary
The human hand is a neuromuscular-skeletal system fundamental for interacting with the external environment and for communicating. A more accurate estimation of the efferent command (neural drive) received by the muscle is obtained investigating the recruitment and firing patterns of motor units, which constitute the final pathway of the nervous system This analysis has been applied to single hand muscles, such as the first dorsal interosseous (FDI) (Enoka and Fuglevand 2001) and abductor digiti minimi (ADM) (Negro et al 2009), typically using intramuscular electromyography. The studies by Weiss (2004) and Huesler (2000) are the only reports that attempted to estimate single motor unit activity from multiple intrinsic and extrinsic muscles, with surface and intramuscular EMG, respectively. These studies were successful in few subjects (four and five respectively) and muscles (respectively 7 and 14, but in the latter case these were only muscles actuating the thumb and the index finger)
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