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Detection of Fatigue under Perceptual Load: Co-registration of Event-related Potentials and Eye Movements

Student: Svetlana Kovalenko

Supervisor: Elena S. Gorbunova

Faculty: Institute for Cognitive Neuroscience

Educational Programme: Cognitive Sciences and Technologies: From Neuron to Cognition (Master)

Final Grade: 10

Year of Graduation: 2024

Fatigue detection is an important task in modern working conditions. Monotony and excessive working hours lead to a decrease in the concentration and efficiency among operators, drivers, pilots, etc. Such violations entail both a decrease in performance, lost in productivity and more serious consequences, for example, car accidents. In this regard, for many years, studies have been carried out to identify markers of fatigue. In particular, both eye tracking and EEG are used for this task (Yamada et al., 2018; Dambros, 2017; Ren et al., 2021). Correlations between characteristics of blinking, saccades, fixations and pupil, as well as changes in rhythms and event related potentials due to fatigue, have been studied in detail (Li et al., 2020; Trejo et al., 2015; Schweizer et al., 2022). Co-registration of these two types of signals could help improve understanding of the occurrence of this functional state. There are two ways of fatigue inducing: manipulate duration or complexity of the task given. This study proposes to focus on complexity of the task that can be ensured by using a high perceptual load stimuli. Aim. The aim of our work is to study the phenomenon of fatigue by manipulating the level of perceptual load. We will detect this state by analyzing firstly reaction time and number of errors and then, eye movements and event-related potentials. Methods. Co-registration of eye movements and EEG during cognitive tasks with different levels of perceptual load (high and low). Results. After the neurophysiological experiment, the hypotheses about changes in subjective sensations, behavioral indicators, oculomotor and brain activity under conditions of different perceptual load were confirmed. Conclusion. This study is a step towards a detailed classification of causes and signs of fatigue. It can be used in various fields for the purpose of timely detection of fatigue.

Full text (added May 19, 2024)

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