Evaluating nonlinear variability of mental fatigue behavioral indices during long‐term attentive task |
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| Authors: | Mahdi Azarnoosh Ali Motie Nasrabadi Mohammad Reza Mohammadi Mohammad Firoozabadi |
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| Affiliation: | 1. Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;2. Biomedical Engineering Department, Faculty of Engineering, Shahed University, Tehran, Iran;3. Psychiatry and Psychology Research Centre (PPRC), Roozbeh Hospital, Tehran University of Medical Science, Tehran, Iran;4. Medical Physics Department, Tarbiat Modares University, Tehran, Iran |
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| Abstract: | This study investigates the behavioral indices of attention. A simple repetitive attentive task that resulted in mental fatigue was used consecutively in four trials. In the first step, reaction time and error responses were recorded to evaluate differences among trials. During the task, subjects showed different responses to stimulations. In the second part, to recognize the strategies, multiple clustering methods such as k‐means and fuzzy c‐means were performed in which behavioral indices and nonlinear features were used. In the last section, mental behavior was identified as a result of the chaotic properties of variations in reaction time. Therefore, the Lyapunov exponent of reaction times was evaluated. Results revealed that behavioral indices could distinguish attention from the occurrence of mental fatigue in trials. In addition, the three strategies used by subjects during the test protocol were assessed. Finally, variation of indices extracted from nonlinear analysis, that is, decrease in degree of chaotic behavior determined the transition from attention to mental fatigue. © 2012 Wiley Periodicals, Inc. Complexity, 2012 |
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| Keywords: | attention mental fatigue complexity nonlinear analysis return map Lyapunov exponent reaction time |
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