Machine Learning Approach to Model Physical Fatigue during Incremental Exercise among Firefighters

Abstract

Physical fatigue is a serious threat to the health and safety of firefighters. Its effects include decreased cognitive abilities and a heightened risk of accidents. Subjective scales and, recently, on-body sensors have been used to monitor physical fatigue among firefighters and safety-sensitive professionals. Considering the capabilities (e.g., noninvasiveness and continuous monitoring) and limitations (e.g., assessed fatiguing tasks and models validation procedures) of current approaches, this study aimed to develop a physical fatigue prediction model combining cardiorespiratory and thermoregulatory measures and machine learning algorithms within a firefighters’ sample. Sensory data from heart rate, breathing rate and core temperature were recorded from 24 participants during an incremental running protocol. Various supervised machine learning algorithms were examined using 21 features extracted from the physiological variables and participants’ characteristics to estimate four physical fatigue conditions: low, moderate, heavy and severe. Results showed that the XGBoosted Trees algorithm achieved the best outcomes with an average accuracy of 82% and accuracies of 93% and 86% for recognising the low and severe levels. Furthermore, this study evaluated different methods to assess the models’ performance, concluding that the group cross-validation method presents the most practical results. Overall, this study highlights the advantages of using multiple physiological measures for enhancing physical fatigue modelling. It proposes a promising health and safety management tool and lays the foundation for future studies in field conditions.

Bioactive Compounds in Citrus reticulata Peel Are Potential Candidates for Alleviating Physical Fatigue through a Triad Approach of Network Pharmacology, Molecular Docking, and Molecular Dynamics Modeling

“…Fatigue, which is defined as difficulty in initiating or maintaining voluntary activities, is a complex physiological and pathological condition that can be categorized into two main types: peripheral fatigue and central fatigue [ 47 , 48 ]. Physical fatigue is an alternative term used for peripheral fatigue, which is characterized by a decline in the physical ability to perform various tasks [ 49 , 50 ]. Fatigue has evolved into a serious public health concern that negatively impacts human health, productivity at work, and quality of life, and about 18.3–27% of the general population is affected by fatigue [ 51 , 52 ].…”

The Effect of Craniosacral Therapy on Blood Levels of Stress Hormones

“…Firefighters are also exposed to heat stress, which is associated with cerebral oxygenation and vascular hemodynamics, and, in turn, can affect cognitive decline [34]. In the firefighting profession, the development of physical fatigue, which can limit the performance of professional activities, also plays an important role [35]. Stress-induced fatigue can affect neuronal activation patterns, altering them and slowing down simple mental operations [36].…”

The Effect of Craniosacral Therapy on Blood Levels of Stress Hormones in Male Firefighter Cadets: A Randomized Clinical Trial

“…Firefighters are also exposed to heat stress, which is associated with cerebral oxygenation and vascular hemodynamics and, in turn, can affect cognitive decline [57]. In the firefighting profession, the development of physical fatigue, which can limit the performance of professional activities, also plays an important role [58]. Stress-induced fatigue can affect neuronal activation patterns, altering them and slowing down simple mental operations [59].…”