A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal

A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification sy...

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Bibliographic Details
Main Authors: Farah Masood, Milan Sharma, Davleen Mand, Shanker Nesathurai, Heather A. Simmons, Kevin Brunner, Dane R. Schalk, John B. Sledge, Hussein A. Abdullah
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
deep learning
machine learning
convolutional neural network
<i>k</i>-nearest neighbors
electromyography
spinal cord injury
Online Access:https://www.mdpi.com/1424-8220/22/21/8455

Internet

https://www.mdpi.com/1424-8220/22/21/8455

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