Selective peripheral nerve recordings from nerve cuff electrodes using convolutional neural networks.

Journal: Journal of neural engineering
PMID:

Abstract

OBJECTIVE: Recording and stimulating from the peripheral nervous system are becoming important components in a new generation of bioelectronics systems. Although neurostimulation has seen a history of successful chronic applications in humans, peripheral nerve recording in humans chronically remains a challenge. Multi-contact nerve cuff electrode configurations have the potential to improve recording selectivity. We introduce the idea of using a convolutional neural network (CNN) to associate recordings of individual naturally evoked compound action potentials (CAPs) with neural pathways of interest, by exploiting the spatiotemporal patterns in multi-contact nerve cuff recordings.

Authors

  • Ryan G L Koh
    Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada. KITE, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, M5G 2A2, Canada.
  • Michael Balas
  • Adrian I Nachman
  • Jose Zariffa