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

Abstract

Classification accuracy and F ₁-score of the best CNN configuration were [Formula: see text] and 0.747 ± 0.114, respectively. The mean Pearson correlation coefficient between the manually measured ankle angle and the angle predicted from the estimated firing rate was [Formula: see text] Significance. The proposed method demonstrates that CAP-based classification can be achieved with high accuracy and can be used to track a physiological meaningful measure (e.g. joint angle). These results provide a promising direction for realizing more effective and intuitive neuroprosthetic systems.