Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue?

Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue?

Surface electromyography (sEMG) is the acquisition, from the skin, of the electrical signal produced by muscle activation. Usually, sEMG is measured through electrodes with electrolytic gel, which often causes skin irritation. Capacitive contactless electrodes have been developed to overcome this li...

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Bibliographic Details
Main Authors: David Perpetuini, Damiano Formenti, Daniela Cardone, Athos Trecroci, Alessio Rossi, Andrea Di Credico, Giampiero Merati, Giampietro Alberti, Angela Di Baldassarre, Arcangelo Merla
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
electromyography (EMG)
muscular fatigue
muscular activity
thermography
machine learning (ML)
Online Access:https://www.mdpi.com/1424-8220/23/2/832

Internet

https://www.mdpi.com/1424-8220/23/2/832

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