Prediction of the Ability to Develop the Relaxation Skill in Drivers of Locomotive Crews

The effectiveness of biofeedback training for the development of relaxation skills using the NeuroDog hardware-software complex is investigated. The relaxation skill is one of the conditions for maintaining the functional state of drivers and assistant drivers of locomotive crews at an optimal level...

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Bibliographic Details
Main Author: N. V. Shcherbina
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2022-12-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
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Online Access:https://doklady.bsuir.by/jour/article/view/3507
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Summary:The effectiveness of biofeedback training for the development of relaxation skills using the NeuroDog hardware-software complex is investigated. The relaxation skill is one of the conditions for maintaining the functional state of drivers and assistant drivers of locomotive crews at an optimal level during a working trip, and it is also one of the factors for a successful inter-trip rest. A multiple regression analysis has been carried out, which allows to predict the indicators characterizing the success of developing the relaxation skill, depending on the severity of psychophysiological and personal indicators of drivers and assistant drivers of locomotive crews. Two regression models have been constructed to explain the dependence of the indicators of developing the skill of achieving relaxation on the psychophysiological and personal characteristics of drivers and assistant drivers of locomotive crews. Models are characterized by sufficient quality. Quality indicators: of the first regression model – coefficient of determination R2 = 0.71 (with F(40, 65) = 4.06, p = 0.00000027), Durbin-Watson statistics d = 1.81, of the second regression model – R2 = 0.75 (with F(49, 56) = 3.51, p = 0.0000043), d = 2.09. To predict the indicators of developing the skill of achieving relaxation, regression equations were obtained depending on the severity of psychophysiological and personal indicators of locomotive crew drivers.
ISSN:1729-7648