Parkinson's disease detection and stage classification: quantitative gait evaluation through variational mode decomposition and DCNN architecture-Reference-Cited by-同舟云学术

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Parkinson's disease detection and stage classification: quantitative gait evaluation through variational mode decomposition and DCNN architecture

Published:2024-08-09 Issue:1 Volume:36 Page:
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

E Balaji¹,Elumalai Vinodh Kumar²,Sandhiya Dhanasekaran³,Swarna Priya R. M.⁴,Shantharajah S. P.⁴

Affiliation:

1. School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India

2. School of Electrical Engineering, Vellore Institute of Technology, Vellore, India

3. Department of Statistics and Data Science, National University of Singapore, Singapore

4. School of Information Technology & Engineering, Vellore Institute of Technology, Vellore, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2024.2383894

Reference44 articles.

1. Gait and tremor investigation using machine learning techniques for the diagnosis of Parkinson disease

2. Automated EEG-based screening of depression using deep convolutional neural network

3. Deep Learning for Ground Reaction Force Data Analysis: Application to Wide-Area Floor Sensing

4. IEEE Sensors Journal

5. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods

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