Detecting and decoding spiking activity from sample populations of single motor neurons using wearable sensors

Ting J, Del Vecchio A, Verma N, Sarma D, Annetta N, Collinger J, Farina D, Weber DJ (2021)

Publication Type: Conference contribution

Publication year: 2021

Conference Proceedings Title: Proceedings Volume 11663, Integrated Sensors for Biological and Neural Sensing

ISBN: 9781510641617

DOI: 10.1117/12.2583313

Abstract

Action potentials generated by motor neurons in the brain and spinal cord carry information about intended and ongoing movement. These biopotentials are typically measured with sensors placed in close proximity to the neurons, providing a direct readout of motor output. For people that have become paralyzed due to spinal cord injury, such readouts can be used to form control signals for operating assistive devices, such as robotic arms and exoskeletons. While most methods for measuring the firing activity of single neurons rely on electrodes that are implanted in the brain, the requirement for surgery poses a barrier to widespread use. Here, we demonstrate that a wearable sensor array can detect residual motor unit activity in muscles paralyzed after severe cervical spinal cord injury. Despite generating no observable hand movement, the volitional recruitment of motor neurons below the level of injury was observed across attempted movements of individual fingers and overt wrist and elbow movements. Subgroups of motor units were coactive during flexion or extension phases of the task. Single digit movement intentions were classified offline from the EMG power (root-mean-square) or motor unit firing rates. Median classification accuracy was 76% when using the root-mean-square of the EMG and 76.5% when using motor unit firing rates. This study provides the first demonstration of a wearable interface for recording and decoding firing rates of motor neurons below the level of spinal cord injury.

Authors with CRIS profile

Alessandro Del Vecchio Juniorprofessur für Neuromuscular Physiology and Neural Interfacing

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) University of Pittsburgh US United States (USA) (US) Carnegie Mellon University US United States (USA) (US) Battelle Memorial Institute US United States (USA) (US)

How to cite

APA:

Ting, J., Del Vecchio, A., Verma, N., Sarma, D., Annetta, N., Collinger, J.,... Weber, D.J. (2021). Detecting and decoding spiking activity from sample populations of single motor neurons using wearable sensors. In SPIE BiOS (Eds.), Proceedings Volume 11663, Integrated Sensors for Biological and Neural Sensing.

MLA:

Ting, Jordyn, et al. "Detecting and decoding spiking activity from sample populations of single motor neurons using wearable sensors." Proceedings of the SPIE BiOS Ed. SPIE BiOS, 2021.

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