Development of Neuro-Degenerative Diseases’ Gait Classification Algorithm Using Convolutional Neural Network and Wavelet Coherence Spectrogram of Gait Synchronization-Reference-Cited by-同舟云学术

Development of Neuro-Degenerative Diseases’ Gait Classification Algorithm Using Convolutional Neural Network and Wavelet Coherence Spectrogram of Gait Synchronization

Published:2022 Issue: Volume:10 Page:38137-38153
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Setiawan Febryan¹^ORCID,Liu An-Bang²,Lin Che-Wei¹^ORCID

Affiliation:

1. Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan City, Taiwan

2. Department of Neurology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and School of Medicine, Tzu Chi University, Hualien City, Taiwan

Funder

Taiwan’s Ministry of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09754696.pdf?arnumber=9754696

Reference61 articles.

1. Implementation of a Deep Learning Algorithm Based on Vertical Ground Reaction Force Time–Frequency Features for the Detection and Severity Classification of Parkinson’s Disease

2. A deep learning-based approach for the classification of gait dynamics in subjects with a neurodegenerative disease;paragliola;Proc SAI Intell Syst Conf,2020

3. The impact of feature extraction for the classification of amyotrophic lateral sclerosis among neurodegenerative diseases and healthy subjects

4. Measuring signal fluctuations in gait rhythm time series of patients with Parkinson's disease using entropy parameters

5. Detection of Parkinson's disease by Shifted One Dimensional Local Binary Patterns from gait

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