Why the study?
Demanding professional tasks can cause mental fatigue, leading to attentional alterations, increased errors, and decreased productivity from deteriorated cognitive control processes.
Does the BAlert mobile application accurately classify fatigue levels in adults?
Does the BAlert mobile application accurately classify fatigue levels in adults?
The BAlert mobile application can classify fatigue levels based on the Stroop effect and heart rate variability with 74% accuracy.
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May support mobile fatigue monitoring; leaves open prospective validation before clinical adoption.
The performance of professional tasks with a high cognitive, emotional, and even physiological demand, can cause a state of mental fatigue, which implies attentional alterations, greater errors in the tasks performed and a decrease in personal and work productivity caused by a deterioration of the cognitive control processes. The present study presents a mobile phone application named BAlert that allows monitoring and controlling the body's fatigue processes based on the scores obtained in the Stroop effect and the heart rate variability. A pilot study has been carried out with a sample of 63 adults who have used the application a total of 942 times. The results allow us to classify the subjects, by logistic regression analysis, in their fatigue levels in 74% of the occasions. These results highlight the importance of this mobile application to control work fatigue processes in different possible scenarios (military, health, sports, business, etc.).
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Marcos et al. (2021) studied this question.
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