Publication:
Classification of Human Emotions Using EEG Signals in a Simulated Environment
Classification of Human Emotions Using EEG Signals in a Simulated Environment
Date
2022-01-01
Authors
Hafiz Halin
Wan Khairunizam Wan Ahmad
Wan Azani Wan Mustafa
Muhajir Ab. Rahim
Zuradzman Mohamad Razlan
Shahriman Abu Bakar
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Abstract
The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
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Keywords
BCI | brain signal | driving simulation | emotions classifications