Deep Learning-Based Approaches for Decoding Motor Intent From Peripheral Nerve Signals

Deep Learning-Based Approaches for Decoding Motor Intent From Peripheral Nerve Signals

Previous literature shows that deep learning is an effective tool to decode the motor intent from neural signals obtained from different parts of the nervous system. However, deep neural networks are often computationally complex and not feasible to work in real-time. Here we investigate different a...

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Bibliographic Details
Main Authors: Diu K. Luu, Anh T. Nguyen, Ming Jiang, Jian Xu, Markus W. Drealan, Jonathan Cheng, Edward W. Keefer, Qi Zhao, Zhi Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Neuroscience
Subjects:
convolutional neural network
deep learning
feature extraction
motor decoding
neuroprosthesis
neural decoder
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.667907/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.667907/full

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