Fatigue Detection Post Physical Activity Using Machine Learning Algorithms

Abstract

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. 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 been enhanced, there is as yet minimal research in the field of fatigue detection post physical activity. In this study the stress would be on objective fatigue detection techniques where the acquisition of physiological data of construction workers is required. The study provides a ground for detection of physiological fatigue based on motion capture data in the form of videos.