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Fatigue Detection Post Physical Activity: A Review
Author(s) -
Ashish Sharma,
Gaurav Sethi
Publication year - 2021
Publication title -
aijr proceedings
Language(s) - English
Resource type - Conference proceedings
ISSN - 2582-3922
DOI - 10.21467/proceedings.114.13
Subject(s) - construction industry , work (physics) , computer science , action (physics) , risk analysis (engineering) , applied psychology , engineering , construction engineering , psychology , medicine , mechanical engineering , physics , quantum mechanics
Construction work is purely effortful and the prevention of injuries at construction job sites is essential for encouraging worker’s well being and health which is generally overlooked at the construction sites. World’s construction industry is one amongst those having unsatisfactory work health issues. A large number of laborers and construction workers have to undergo fatigue risk at their job place as fatigue increases the risk of injury among construction workers. This paper describes the current state of the art of the research carried out in case of fatigue assessment after performing some physical activity providing an insight into fatigue, its detection and an overview of the causes of risk fatigue and its countermeasures. A number of subjective and objective fatigue assessment approaches have been used that have further stimulated the inclusion of latest and advanced approaches for fatigue detection. Although individual’s knowledge regarding the fatigue detection approaches has enhanced, there is as yet minimal research in the field of fatigue detection post physical activity at construction sites. This article provides a novel deep action recognition approach using deep extension based equilibrium with capsule auto encoder network for the detection of physiological fatigue among construction workers. The proposed method was tested on the dataset collected at the local construction sites in the form of videos.

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