Fatigue detection through physiological assessment during real-life occupational situations: Preliminary results

• Autor(a) principal: Bustos, D
• Data de Publicação: 2021
• Outros Autores: Guedes, J. C., Pratas, P, Vaz, M, Costa, JT, Fernandes, R, João Santos Baptista
• Tipo de documento: Livro
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/148014

<jats:p>Background: Fatigue is a significant health and safety-related problem among workers. In general, it decreases performance and physical strength, causing incidents and accidents in operational situations. During military activities, soldiers often encounter severe conditions, which combined lead to fatigue manifestations affecting their health and performance. Continuous monitoring of their overall health status would prevent its adverse effects. Objective: This work aimed to present the preliminary results of a retrospective assessment of military training physiological recordings using an alert-based fatigue detection algorithm to validate its accurate functioning. Methods: Three case studies from soldiers participating in military training tests were recruited for evaluation. The referred algorithm was developed to manage fatigue through the combined assessment of physiological variables and determine different fatigue levels warnings to advisetimely interventions and prevent potential health impact. Each examined case included the continuous recording of heart rate, breathing rate and core temperature. The algorithm translated physiological sensory data into minute alarms according to fatigue levels determined through the conjunction of normative and related research criteria. Results and Discussion: Outcomes revealed that the algorithm could evidence the different stages of training and the resulting physical demands on soldiers using their physiological response throughout the exercises. Retrieved fatigue alarms showed the high physiological cost of military practices and helped to overview the impact of each training period. Finally, results also demonstrated the importance of individual and contextualised assessment for accurately characterise the subject's fatigue status. Conclusions: It is concluded that the developed decision model can improve the management of real-time fatigue, allowing early detection of potential indicators of further physical impairments. Furthermore, it can lead to the enhancement of work-rest cycles, not only for tactical personnel but also for any safety-sensitive occupation. For future work, its validity will be tested through more participants, and other variableswill be added to improve its accuracy.</jats:p>