Muscle Fatigue Analysis by Visualization of Dynamic Surface EMG Signals Using Markov Transition Field-Reference-Cited by-同舟云学术

Muscle Fatigue Analysis by Visualization of Dynamic Surface EMG Signals Using Markov Transition Field

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Sasidharan Divya¹,G Venugopal²,Ramakrishnan S³

Affiliation:

1. Research Scholar with NSS College of Engineering Palakkad (Affliated to APJ Abdul Kalam Technological University),Kerala,India

2. NSS College of Engineering Palakkad,(Affliated to APJ Abdul Kalam Technological University),working as Professor with the Instrumentation and Control Engineering Department,Kerala,India

3. Professor with the Biomedical Engineering Group Department of Applied Mechanics,IIT Madras,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871981.pdf?arnumber=9871981

Reference17 articles.

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3. Sequential behavioral data processing using deep learning and the markov transition field in online fraud detection;zhang;Arxiv Prepr,2018

4. Emotion stimuli-based surface electromyography signal classification employing Markov transition field and deep neural networks;li;Measurement,2021

5. Analysis of Dynamics of EMG Signal Variations in Fatiguing Contractions of Muscles Using Transition Network Approach

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