Evaluating nonlinear variability of mental fatigue behavioral indices during long‐term attentive task

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.

Boredom in the Workplace

“…Such results parallel similar results in vigilance studies, where reaction times, false alarms, and stimuli missed increase over time, and such changes in performance are likely an indicator for mental fatigue, which could be influenced by boredom (Azarnoosh, Nasrabadi, Mohammadi, & Firoozabadi, 2012;Ballard, 1996;Scerbo, 1998b). However, one problem with the use of implicit measures is their infrequency.…”

Distribution of human response times

“…It must be emphasized that while the GIGa framework, theoretically motivated by the dynamics of complex networks, provides for a clear analytical description of distribution's properties as a function of its parameters, our tail fitting technique apropos power‐law tails and our conjecture of the relationship between the progressive task complexity and distribution's half‐width and modal PDF are not conceptually tied to the specifics of the GIGa and could be readily applied to analysis of alternative frameworks. Toward that end, we point out to a number of studies that attack similar problems with a variety of approaches .…”

Attention Detection by Heartbeat and Respiratory Features from Radio-Frequency Sensor

“…The trend is reasonable since it took initial 1–2 min for participants to learn the game and then they got drowsy or tired as the game continued for a longer period, based on the reviews noted earlier. This definition of attention has limited scope as it does not include RT, which is shown to be related to attention and fatigue in earlier work [ 53 ].…”