Deep Learning Movement Intent Decoders Trained With Dataset Aggregation for Prosthetic Limb Control

Abstract

The short-term and long-term performances of MLP- and CNN-based decoders trained with DAgger demonstrated their potential to provide more accurate and naturalistic control of prosthetic hands than alternate approaches.