Can data-driven supervised machine learning approaches applied to infrared thermal imaging data estimate muscular activity and fatigue?

HIGHLIGHTS

SUMMARY

Novel techniques based on complexity analysis and machine_learning (ML) have been applied to the analysis of EMG data (for a recent review, see Rampichini et_al, 2020 ). The aim of the study is not to measure the EMG signal from skin temperature variations assessed through IRI, but to find correlations between metrics evaluated from the EMG signal and IRI signal features, although the two processes are of a different physiological nature. The IRI measurements were performed in accordance with the guidelines provided by Moreira et_al, 2017. Regarding the placement of the thermal camera, Vardasca et_al . . .

 



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