An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors
This study aimed to develop an intellectual and analytical platform for assessing the psychophysiological load on flight instructors in a flight school (general aviation). As part of this study, an information model for evaluating the working environment’s load based on noise levels was developed, a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/11/5917 |
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| author | Miroslav Kelemen Volodymyr Polishchuk Martin Kelemen Miroslav Badida Marek Moravec |
| author_facet | Miroslav Kelemen Volodymyr Polishchuk Martin Kelemen Miroslav Badida Marek Moravec |
| author_sort | Miroslav Kelemen |
| collection | DOAJ |
| description | This study aimed to develop an intellectual and analytical platform for assessing the psychophysiological load on flight instructors in a flight school (general aviation). As part of this study, an information model for evaluating the working environment’s load based on noise levels was developed, a model to predict individual psychophysiological load was created, an expert model to assess mental health was established, and a hybrid model was devised to determine the overall psychophysiological load on an instructor while performing their duties. Noise load was measured during flights with two aircraft (Zlín Z43 and Diamond DA-40 TDI), resulting in the acquisition of 4,361,300 data points. This dataset was collected during two data acquisition sessions for each aircraft, encompassing three phases of flight: takeoff, in-flight, and landing. During the flight, noise measurements were conducted based on five indicators: sound pressure, fluctuation strength, roughness, sharpness, and tonality. Based on the measured data, the platform was verified and configured, and example evaluations were demonstrated. This study employed modern methods of intelligent data analysis, utilizing both univariate and multivariate membership functions. The developed platform incorporates quantitative dynamic data obtained from devices measuring psychophysiological load, integrating professional mental health assessments and predicting dynamic work environment indicators for modeling load trends. Early detection of critical load levels helps protect the health of flight instructors, thus creating a safe working environment for training new pilots. |
| format | Article |
| id | doaj-art-c2cfcfb35f0c4d34b82bdd52af0be83d |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-c2cfcfb35f0c4d34b82bdd52af0be83d2025-08-20T03:46:38ZengMDPI AGApplied Sciences2076-34172025-05-011511591710.3390/app15115917An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight InstructorsMiroslav Kelemen0Volodymyr Polishchuk1Martin Kelemen2Miroslav Badida3Marek Moravec4Faculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, SlovakiaFaculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, SlovakiaFaculty of Aeronautics, Technical University of Košice, Rampová 7, 041 21 Košice, SlovakiaFaculty of Mechanical Engineering, Technical University of Košice, Letná 1/9, 042 00 Košice, SlovakiaFaculty of Mechanical Engineering, Technical University of Košice, Letná 1/9, 042 00 Košice, SlovakiaThis study aimed to develop an intellectual and analytical platform for assessing the psychophysiological load on flight instructors in a flight school (general aviation). As part of this study, an information model for evaluating the working environment’s load based on noise levels was developed, a model to predict individual psychophysiological load was created, an expert model to assess mental health was established, and a hybrid model was devised to determine the overall psychophysiological load on an instructor while performing their duties. Noise load was measured during flights with two aircraft (Zlín Z43 and Diamond DA-40 TDI), resulting in the acquisition of 4,361,300 data points. This dataset was collected during two data acquisition sessions for each aircraft, encompassing three phases of flight: takeoff, in-flight, and landing. During the flight, noise measurements were conducted based on five indicators: sound pressure, fluctuation strength, roughness, sharpness, and tonality. Based on the measured data, the platform was verified and configured, and example evaluations were demonstrated. This study employed modern methods of intelligent data analysis, utilizing both univariate and multivariate membership functions. The developed platform incorporates quantitative dynamic data obtained from devices measuring psychophysiological load, integrating professional mental health assessments and predicting dynamic work environment indicators for modeling load trends. Early detection of critical load levels helps protect the health of flight instructors, thus creating a safe working environment for training new pilots.https://www.mdpi.com/2076-3417/15/11/5917flight trainingintellectual–analytical platformflight instructornoise levelexpert assessmentmental health |
| spellingShingle | Miroslav Kelemen Volodymyr Polishchuk Martin Kelemen Miroslav Badida Marek Moravec An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors Applied Sciences flight training intellectual–analytical platform flight instructor noise level expert assessment mental health |
| title | An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors |
| title_full | An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors |
| title_fullStr | An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors |
| title_full_unstemmed | An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors |
| title_short | An Intellectual–Analytical Platform for Assessing the Psychophysiological Load on Flight Instructors |
| title_sort | intellectual analytical platform for assessing the psychophysiological load on flight instructors |
| topic | flight training intellectual–analytical platform flight instructor noise level expert assessment mental health |
| url | https://www.mdpi.com/2076-3417/15/11/5917 |
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