ELECTROENCEPHALOGRAPHY SIGNAL ANALYSIS FOR EARLY DETECTION OF VISUALLY INDUCED MOTION SICKNESS

• Main Author: Restu Fardian Suwandi, Galih
• Format: Dissertations
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/82786
• Institution: Institut Teknologi Bandung

The use of virtual reality technology has experienced a rapid increase in the aftermath of the COVID-19 pandemic. This growth encompasses a rise in users and a broader range of applications. Originally confined to the entertainment industry, virtual reality technology has expanded into other sectors such as education, healthcare, tourism, and beyond. This evolution positions virtual reality technology as a crucial element of future human life. However, behind this progress lies a fundamental concern regarding human interaction and virtual reality technology. This concern is associated with developing symptoms similar to motion sickness following virtual reality interaction, known as visually induced motion sickness. This poses a significant obstacle to the advancement of virtual reality technology. To tackle this issue, efforts are underway to study these symptoms. One approach involves the evaluation of various physiological parameters of the human body. This research will specifically focus on analyzing brainwave electrical activity. Electroencephalography modalities will be used to measure the electrical signals in the brain when an individual engages in a virtual reality scenario. This study aims to establish the correlation between brain wave dynamics and virtual reality experience. This research consists of five experiments, including one preliminary and four main experiments. The preliminary experiment serves as a baseline for the subsequent experiments. The main experiments are designed based on the sensory conflict theory, particularly for motion sickness. The first experiment evaluated the impact of a Faraday cage on recorded electroencephalography signals and the influence of using a head-mounted display on these signals. The results of this experiment will determine the measurement parameters for the following experiments. The second experiment compared the effects of different fields of view presented through virtual reality media on motion sickness symptoms. The third experiment aimed to compare the effects of variations in physical motion parameters of virtual reality content. The fourth experiment sought to observe the effects of frame rate and video playback speed. The fifth experiment investigated how incorporating optokinetic elements in virtual reality videos affects motion sickness symptoms. The EEG signals underwent preprocessing, including filtering and feature extraction, focusing on calculating spectral power density. The results of the spectral power density were then analyzed in relation to the features of the virtual reality display. A qualitative analysis was conducted by administering a simulator sickness questionnaire for comparison. The use of Virtual Reality (VR) through Head-Mounted Display (HMD) has been found to induce greater Visually Induced Motion Sickness (VIMS) compared to traditional screen viewing. This was supported by noticeable Power Spectral Density (PSD) changes when participants engaged with VR content using an HMD. The complexity of motion and the experience of circular vection significantly impacted the level of VIMS reported by participants. Additionally, deviations from normal VR video frame rates and speeds were observed to have a notable impact on VIMS, particularly when the frame rate dropped to 15 fps. The optokinetic aspect also impacted the level of VIMS, with the frequency of pattern repetition proving more influential than the number of patterns in the video. The cognitive load experienced by subjects was reflected in the beta/alpha power ratio, which exhibited a positive correlation with the perceived level of VIMS. Conversely, the stress level experienced by subjects was indicated by the theta/beta power ratio, showing a negative correlation with the perceived level of VIMS. Increased cognitive load and stress levels typically manifest in certain aspects of the video, such as more complex motion characteristics, a decrease in frame rate to 15 fps, an increase in video speed, and an increase in optokinetic pattern repetition frequency. This study observed that providing VR viewing increased the occurrence of VIMS symptoms, as confirmed by questionnaire results and EEG signal analysis. The research demonstrates the correlation between brain wave signal characteristics and the symptoms of motion sickness induced by virtual reality content. These findings could serve as a foundation for quantitatively assessing the adverse effects of using virtual reality technology, particularly visually induced motion sickness. As a result, this research can potentially contribute to the advancement of virtual reality technology.