Resource-Efficient Neural Network Architectures for Classifying Nerve Cuff Recordings on Implantable Devices.
Journal:
IEEE transactions on bio-medical engineering
PMID:
37672367
Abstract
BACKGROUND: Closed-loop functional electrical stimulation can use recorded nerve signals to create implantable systems that make decisions regarding nerve stimulation in real-time. Previous work demonstrated convolutional neural network (CNN) discrimination of activity from different neural pathways recorded by a high-density multi-contact nerve cuff electrode, achieving state-of-the-art performance but requiring too much data storage and power for a practical implementation on surgically implanted hardware.