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Objective assessment of fatigue among aviation personnel using a bio-mathematical model: An experimental study.
Mohapatra, Sudhanshu Shekhar; Sinha, Biswajit; Tripathy, Niraj Kumar; Ghosh, Devdeep.
Afiliación
  • Mohapatra SS; Professor (Aviation Medicine), INS Shikra, Colaba, Mumbai, India.
  • Sinha B; Scientist "F" & Head (Space & Environment Physiology), Institute of Aerospace Medicine (IAF), Bengaluru, India.
  • Tripathy NK; Chief Research Officer, Research Department, Institute of Aerospace Medicine (IAF), Bengaluru India.
  • Ghosh D; SMO, 47 Wing, Medical Department, Air Force Station, Thanjavur SMC, Thanjavur, Tamilnadu, India.
Med J Armed Forces India ; 80(2): 217-223, 2024.
Article en En | MEDLINE | ID: mdl-38525454
ABSTRACT

Background:

There are many subjective and objective tools to detect, assess, and quantify fatigue. This study is a novice attempt to assess the occupational fatigue among the aviation personnel employing a computerized work-rest schedule tool integrated with actigraphy.

Methods:

Thirty-eight aviation personnel were assessed for their sleep by using an actigraphy device. A work-rest scheduling software program called Fatigue Avoidance Scheduling Tool (FAST) was used to obtain fatigue parameters like Fatigue Risk Time (FRT), Fatigue Free Time (FFT), and Fatigue Free Occupational Time (FFOT).

Results:

The percentages of crew having a night sleep of the duration of more than 6 hours were 50% (Mon), 44.7% (Tue), 44.7% (Wed), and 47.3% (Thu) for weekdays and 65.8% (Fri), 57.9% (Sat), and 57.9% (Sun) for the weekend. There was a gradual increase in FRT, FFT, and FFOT from Day 1 to Day 5 of the week, and the differences were statistically significant.

Conclusion:

Increase in the FRT with a reciprocal drop of FFT and FFOT was observed with the progress of the week. Total Sleep Time (TST) of less than 8 hours could be the reason for a gradual increase in sleep debt, leading to fatigue depicted as increase in fatigue risk parameter FRT and gradual decrease in fatigue preventing parameters like FFT and FFOT. It was further confirmed by regression analysis in which TST was found to be a statistically significant predictor for all fatigue parameters. Regression equation for FFOT as 498.53 + (0.39 x TST) - (58.8 x Day of the week) can be used.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Med J Armed Forces India Año: 2024 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Med J Armed Forces India Año: 2024 Tipo del documento: Article País de afiliación: India
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