{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T17:15:59Z","timestamp":1792343759587,"version":"4.4.0"},"reference-count":61,"publisher":"Georg Thieme Verlag KG","issue":"04","license":[{"start":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T00:00:00Z","timestamp":1716940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sleep Sci"],"published-print":{"date-parts":[[2024,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The present study used four different methods to estimate fatigue. Forty-seven volunteers (45 men and 2 women), 41.3\u2009\u00b1\u20097.5 years old, truck operators for 11.5\u2009\u00b1\u20096.0 years, were included. All participants accepted the invitation to be included in the study. Actigraphy and core temperature were evaluated. The 5-minute psychomotor vigilance test, the Karolinksa Sleepiness Scale (KSS), and the postural assessment using the Light Sonometer\u2122 (Belo Horizonte, Minas Gerais, Brazil) were performed. Fatigue prediction was performed using the Fatigue Avoidance Scheduling Tool (FAST) program. In response to the Pittsburgh Sleep Quality Index (PSQI), 51.06% had good sleep quality and 48.94% had poor sleep quality with an average efficiency of 81.6%. In response to the actigraphy, workers slept an average of 7.2\u2009hours a day with 93.5% efficiency. The workers' core body temperature (CBT) cosinor analysis showed a preserved circadian curve. Core body temperature showed differences between the 6\u2009hours worked in each shift. Similarly, the light sound level meter showed lower risk scores for fatigue in day shifts. Only the variable of the fastest 10% of the Psychomotor Vigilance Test (PVT) showed worse results, while no significant differences were observed by the KSS. The risk analysis by FAST showed a strong influence of the circadian factor. In conclusion, each method has positive and negative points, and it is up to the evaluator\/manager to identify the method that best suits the purpose of the evaluation, as well as the local culture and conditions. We recommend using different methods of risk assessment and management in combination with fatigue prediction by Sonometer as well as carrying out assessments, which enable researchers to estimate performance and fatigue throughout the working day, since these may change over the duration of the working day.<\/jats:p>","DOI":"10.1055\/s-0044-1782175","type":"journal-article","created":{"date-parts":[[2024,5,29]],"date-time":"2024-05-29T23:23:32Z","timestamp":1717025012000},"page":"e339-e349","source":"Crossref","is-referenced-by-count":3,"title":["Comparative Analysis of Methods of Evaluating Human Fatigue"],"prefix":"10.1055","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3896-2208","authenticated-orcid":false,"given":"Marco T\u00falio","family":"de Mello","sequence":"additional","affiliation":[{"name":"Department of Sports, Universidade Federal de Minas Gerais, Belo Horizonte, MG, 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