Channel Selection of EEG-Based Cybersickness Recognition during Playing Video Game Using Correlation Feature Selection (CFS)

Khoirunnisaa, Alfi Zuhriya; Pane, Evi Septiana; Wibawa, Adhi Dharma; Purnomo, Mauridhi Hery

doi:10.1109/ibiomed.2018.8534877

Cited by 13 publications

(7 citation statements)

References 9 publications

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“…The authors observed a higher detection accuracy when a narrow kernel shape was applied rather than considering a broader range of power changes. In addition, EEG features extracted from the latter part of the VR experience showed higher detection performance (Khoirunnisaa et al 2018;Kim et al 2019a;Ko et al 2013). This result might come from the fact that a longer duration of VR can cause more severe discomfort (Chang et al 2020;Rebenitsch and Owen 2016).…”

Section: Feature Extractionmentioning

confidence: 96%

“…These locations are well-known places for the reference electrode because they are electrically stabilized but linked to the cortical area. In some cases, a particular spherical region, such as the frontal or parietal area, was chosen for the re-referencing (Ahn et al 2020;Khoirunnisaa et al 2018;Wu et al 2020).…”

Section: Preprocessingmentioning

confidence: 99%

“…Various approaches such principal component analysis (PCA), and correlation-based feature selection (CFS) were used for the feature selection. Several studies have tested different selection methods to narrow down the EEG features highly related to the subjective level of cybersickness (Khoirunnisaa et al 2018;Wei et al 2011). The results showed that spectral changes in the frontal lobe were closely related to cybersickness.…”

Section: Feature Selectionmentioning

confidence: 99%

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Brain activity during cybersickness: a scoping review

Chang

Billinghurst

2023

Virtual Reality

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Virtual reality (VR) experiences can cause a range of negative symptoms such as nausea, disorientation, and oculomotor discomfort, which is collectively called cybersickness. Previous studies have attempted to develop a reliable measure for detecting cybersickness instead of using questionnaires, and electroencephalogram (EEG) has been regarded as one of the possible alternatives. However, despite the increasing interest, little is known about which brain activities are consistently associated with cybersickness and what types of methods should be adopted for measuring discomfort through brain activity. We conducted a scoping review of 33 experimental studies in cybersickness and EEG found through database searches and screening. To understand these studies, we organized the pipeline of EEG analysis into four steps (preprocessing, feature extraction, feature selection, classification) and surveyed the characteristics of each step. The results showed that most studies performed frequency or time-frequency analysis for EEG feature extraction. A part of the studies applied a classification model to predict cybersickness indicating an accuracy between 79 and 100%. These studies tended to use HMD-based VR with a portable EEG headset for measuring brain activity. Most VR content shown was scenic views such as driving or navigating a road, and the age of participants was limited to people in their 20 s. This scoping review contributes to presenting an overview of cybersickness-related EEG research and establishing directions for future work.

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Section: Feature Extractionmentioning

confidence: 96%

Section: Preprocessingmentioning

confidence: 99%

Section: Feature Selectionmentioning

confidence: 99%

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Brain activity during cybersickness: a scoping review

Chang

Billinghurst

2023

Virtual Reality

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“…Some papers reported that the gamma-band power was positively correlated with the level of cybersickness (Lin et al 2002;Wibawa et al 2019). Other papers recommended that beta and theta frequencies were reliable for detecting cybersickness (Pane et al 2018;Khoirunnisaa et al 2018). Event-based potentials (ERPs) analysis was also commonly applied; it is a measure of brain activities during a potential cybersickness triggered event or time scope (such as turning, or translational acceleration, etc.).…”

Section: Objective Measurementsmentioning

confidence: 99%

A review of cybersickness in head-mounted displays: raising attention to individual susceptibility

2022

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Cybersickness still poses a significant challenge to the widespread usage of virtual reality, leading to different levels of discomfort and potentially breaking the immersive experience. Researchers have attempted to discover the possible fundamental causes of cybersickness for years. Despite the longstanding interest in the research field, inconsistent results have been drawn on the contributing factors and solutions to combating cybersickness. Moreover, little attention has been paid to individual susceptibility. A consolidated explanation remains under development, requiring more empirical studies with robust and reproducible methodologies. This review presents an integrated survey connecting the findings from previous review papers and the state of the art involving empirical studies and participants. A literature review is then presented, focusing on the practical studies of different contributing factors, the pros and cons of measurements, profiles of cybersickness, and solutions to reduce this phenomenon. Our findings suggest a lack of considerations regarding user susceptibility and gender balance in between groups studies. In addition, incongruities among empirical findings raised concerns. We conclude by suggesting points of insights for future empirical investigations.

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“…The results showed a positive correlation between the participants' nausea scores and the left inferior frontal activity. In addition, Khoirunnisaa et al (2018) performed correlation feature selection to determine the optimal channel location for identifying cybersickness-related EEG. The author concluded that the beta frequency band in the frontal area is a promising location for user discomfort.…”

Section: Previous Findings In Cybersickness-related Eegmentioning

confidence: 99%

Identifying physiological correlates of cybersickness using heartbeat-evoked potential analysis

Chang

Kim

2022

Virtual Reality

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Many studies have consistently proven that repeatedly watching virtual reality (VR) content can reduce cybersickness. Moreover, the discomfort level decreases when the VR content includes an unusual orientation, such as an inverted scene. However, few studies have investigated the physiological changes during these experiences. The present study aimed to identify psychophysiological correlates, especially the neural processing, of cybersickness. Twenty participants experienced two types of VR orientation (upright and inverted), which were repeated three times. During the experience, we recorded the participants’ subjective levels of discomfort, brain waves, cardiac signals, and eye trajectories. We performed a heartbeat-evoked potential (HEP) analysis to elucidate the cortical activity of heartbeats while experiencing cybersickness. The results showed that the severity of cybersickness decreased as the participants repeatedly watched the VR content. The participants also reported less nausea when watching the inverted orientation. We only found a significant suppression at the fronto-central HEP amplitudes in the upright orientation for the physiological changes. This study provides a comprehensive understanding of bodily responses to varying degrees of cybersickness. In addition, the HEP results suggest that this approach might reflect the neural correlates of transient changes in heartbeats caused by cybersickness.

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Channel Selection of EEG-Based Cybersickness Recognition during Playing Video Game Using Correlation Feature Selection (CFS)

Cited by 13 publications

References 9 publications

Brain activity during cybersickness: a scoping review

Brain activity during cybersickness: a scoping review

A review of cybersickness in head-mounted displays: raising attention to individual susceptibility

Identifying physiological correlates of cybersickness using heartbeat-evoked potential analysis

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