A Generalized Framework for the Study of Spinal Motor Neurons Controlling the Human Hand During Dynamic Movements

Cakici AL, Oßwald M, Souza de Oliveira D, Braun D, Simpetru RC, Kinfe TM, Eskofier B, Del Vecchio A (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2022-July

Pages Range: 4115-4118

Conference Proceedings Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Event location: Glasgow, GBR

ISBN: 9781728127828

DOI: 10.1109/EMBC48229.2022.9870914

Abstract

The human hand possesses a large number of degrees of freedom. Hand dexterity is encoded by the discharge times of spinal motor units (MUs). Most of our knowledge on the neural control of movement is based on the discharge times of MUs during isometric contractions. Here we designed a noninvasive framework to study spinal motor neurons during dynamic hand movements with the aim to understand the neural control of MUs during sinusoidal hand digit flexion and extension at different rates of force development. The framework included 320 high-density surface EMG electrodes placed on the forearm muscles, with markerless 3D hand kinematics extracted with deep learning, and a realistic virtual hand that displayed the motor tasks. The movements included flexion and extension of individual hand digits at two different speeds (0.5 Hz and 1.5 Hz) for 40 seconds. We found on average 4.7-1.7 MUs across participants and tasks. Most MUs showed a biphasic pattern closely mirroring the flexion and extension kinematics. Indeed, a factor analysis method (non-negative matrix factorization) was able to learn the two components (flexion/extension) with high accuracy at the individual MU level ({R}=0.87-0.12). Although most MUs were highly correlated with either flexion or extension movements, there was a smaller proportion of MUs that was not task-modulated and controlled by a different neural module (7.1% of all MUs with {R} < 0.3). This work shows a noninvasive visually guided framework to study motor neurons controlling the movement of the hand in human participants during dynamic hand digit movements.

Authors with CRIS profile

Marius Oßwald Department Artificial Intelligence in Biomedical Engineering Daniela Souza de Oliveira Department Artificial Intelligence in Biomedical Engineering Dominik Braun Juniorprofessur für Neuromuscular Physiology and Neural Interfacing Thomas Mehari Kinfe Professur für Neurochirurgie mit dem Schwerpunkt Funktionelle Stereotaktische Neurochirurgie Björn Eskofier Machine Learning and Data Analytics Lab Alessandro Del Vecchio Juniorprofessur für Neuromuscular Physiology and Neural Interfacing

How to cite

APA:

Cakici, A.L., Oßwald, M., Souza de Oliveira, D., Braun, D., Simpetru, R.C., Kinfe, T.M.,... Del Vecchio, A. (2022). A Generalized Framework for the Study of Spinal Motor Neurons Controlling the Human Hand During Dynamic Movements. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 4115-4118). Glasgow, GBR: Institute of Electrical and Electronics Engineers Inc..

MLA:

Cakici, Andre L., et al. "A Generalized Framework for the Study of Spinal Motor Neurons Controlling the Human Hand During Dynamic Movements." Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022, Glasgow, GBR Institute of Electrical and Electronics Engineers Inc., 2022. 4115-4118.

BibTeX: Download