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OperatorEYEVP: Operator Dataset for Fatigue Detection Based on Eye Movements, Heart Rate Data, and Video Information.

Svetlana Kovalenko¹, Anton Mamonov², Vladislav Kuznetsov³

¹Institute of Cognitive Neuroscience, HSE University, Moscow 101000, Russia.

Sensors (Basel, Switzerland)

|July 14, 2023

Summary

This summary is machine-generated.

This study introduces a new dataset for fatigue detection, crucial for accident prevention systems. Analysis shows eye-tracking data correlates with choice reaction time, indicating fatigue presence.

Keywords:

HRV (heart rate variability)dataset eye tracking face and head video fatigue gaze tracking

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Area of Science:

Physiological and behavioral indicators for fatigue detection.
Development of preventive systems for accident prevention.

Background:

Fatigue detection is critical for systems like driver and operator monitoring.
Objective physiological and behavioral indicators are needed for accurate fatigue assessment.
Existing public datasets lack comprehensive data for fatigue detection model development.

Purpose of the Study:

To create a novel dataset for fatigue detection research.
To identify reliable physiological and behavioral indicators of fatigue.
To evaluate the suitability of existing datasets for fatigue detection.

Main Methods:

Collected multi-modal data (eye-tracking, video, heart rate) from 10 participants over 8 days.
Participants engaged in various tasks simulating everyday activities (e.g., choice reaction time, reading).
Analyzed public datasets and the newly collected data for fatigue detection suitability.

Main Results:

Existing public datasets were found insufficient for comprehensive fatigue detection.
The newly recorded dataset demonstrates utility for fatigue studies.
Correlations between eye-tracking data and choice reaction time indicate fatigue presence.

Conclusions:

A new, multi-modal dataset was successfully created for fatigue detection.
The dataset supports the identification of fatigue indicators.
Eye-tracking data shows promise as a fatigue indicator in conjunction with behavioral tasks.