Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies.

We analyze and interpret arm and forearm muscle activity in relation with the kinematics of hand pre-shaping during reaching and grasping from the perspective of human synergistic motor control.Ten subjects performed six tasks involving reaching, grasping and object manipulation. We recorded electromyographic (EMG) signals from arm and forearm muscles with a mix of bipolar electrodes and high-density grids of electrodes.

Neuromorphic Decoding of Spinal Motor Neuron Behaviour During Natural Hand Movements for a New Generation of Wearable Neural Interfaces.

We propose a neuromorphic framework to process the activity of human spinal motor neurons for movement intention recognition. This framework is integrated into a non-invasive interface that decodes the activity of motor neurons innervating intrinsic and extrinsic hand muscles. One of the main limitations of current neural interfaces is that machine learning models cannot exploit the efficiency of the spike encoding operated by the nervous system.

Synergistic Organization of Neural Inputs from Spinal Motor Neurons to Extrinsic and Intrinsic Hand Muscles.

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons.

Non-invasive analysis of motor neurons controlling the intrinsic and extrinsic muscles of the hand.

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.

A high-density surface EMG framework for the study of motor neurons controlling the intrinsic and extrinsic muscles of the hand.

We propose a framework based on high-density surface electromyography (HD-sEMG) to identify the neural drive to muscles controlling the human hand. High-density (320 channels) sEMG signals were recorded concurrently from intrinsic (the four dorsal interossei and thenar) and extrinsic (forearm) hand muscles and then decomposed into the constituent trains of motor unit (MU) action potentials. The participants performed pinch tasks with simultaneous activation of the thumb and one of the other fingers with sinusoidal force variations.