감성과학 (Science of Emotion and Sensibility)

  • 제22권3호
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  • Pages.3-20
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  • 2019
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  • 1226-8593(pISSN)
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  • 2383-613X(eISSN)
한국감성과학회 (Korean Society for Emotion and Sensibility)
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128 채널 뇌파를 이용한 사이버멀미 평가법 개발

Development of a Method of Cybersickness Evaluation with the Use of 128-Channel Electroencephalography

  • 한동욱 (과학기술연합대학원대학교 한국표준과학연구원 캠퍼스 의학물리학) ;
  • 이동현 (과학기술연합대학원대학교 한국표준과학연구원 캠퍼스 의학물리학) ;
  • 지경하 (충남대학교 의류학과) ;
  • 안봉영 (한국표준과학연구원 의료융합표준센터) ;
  • 임현균 (한국표준과학연구원 의료융합표준센터)
  • 투고 : 2019.06.20
  • 심사 : 2019.07.05
  • 발행 : 2019.09.30
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초록

가상현실 기술이 발전하면서 다양한 영역에서 여러 목적으로 활용되고 있다. 하지만 사용자로부터 메스꺼움, 어지러움 등과 같은 멀미 증상에 대한 부작용도 함께 보고되고 있다. 이런 멀미 증상을 사이버멀미라고 말하며, 사용자에게 불편을 야기시켜 불쾌감과 스트레스와 같은 부정적 영향을 줄 수 있으며, 현재 사이버멀미의 발생 원인과 해결책에 관한 공식적인 표준이 없다. 본 연구에서는 이런 한계점을 극복하기 위해 정량적, 객관적 사이버멀미 평가법을 제안하였다. 10명의 20대 남성 대상으로 이동과 회전을 하는 가상현실을 경험하게 하면서 128채널의 뇌파를 측정하였다. 11개 영역에서 Delta와 Alpha 상대 파워를 계산하고, ROC curve를 통해 area under the ROC curve (AUC)가 가장 높은 값을 가지는 다중회귀모형을 도출하였다. 이렇게 도출한 다중회귀모형은 11개의 설명변수로 피험자가 응답한 사이버멀미의 정도와 비교하여 95.1 % (AUC = 0.951)의 정확성으로 사이버멀미를 구분하는 것이 가능함을 알 수 있었다. 이러한 결과를 정리하면 본 연구에서는 128 채널의 뇌파를 통해 멀미에 대한 객관적 반응을 확인하였으며, 뇌의 특정부위에서 반응이 있는 것으로 나타났다. 본 연구 결과와 분석법을 활용하면 추후 사이버멀미 관련 연구에 도움이 될 수 있을 것으로 기대된다.

With advancements in technology of virtual reality, it is used for various purposes in many fields such as medical care and healthcare, but as the same time there are also increasing reports of nausea, eye fatigue, dizziness, and headache from users. These symptoms of motion sickness are referred to as cybersickness, and various researches are under way to solve the cybersickness problem because it can cause inconvenience to the user and cause adverse effects such as discomfort or stress. However, there is no official standard for the causes and solutions of cybersickness at present. This is also related to the absence of tools to quantitatively measure the cybersickness. In order to overcome these limitations, this study proposed quantitative and objective cybersickness evaluation method. We measured 128-channel EEG waves from ten participants experiencing visually stimulated virtual reality. We calculated the relative power of delta and alpha in 11 regions (left, middle, right frontal, parietal, occipital and left, right temporal lobe). Multiple regression models were obtained in a stepwise manner with the motion sickness susceptibility questionnaire (MSSQ) scores indicating the susceptibility of the subject to the motion sickness. A multiple regression model with the highest under the area ROC curve (AUC) was derived. In the multiple regression model derived from this study, it was possible to distinguish cybersickness by accuracy of 95.1% with 11 explanatory variables (PD.MF, PD.LP, PD.MP, PD.RP, PD.MO, PA.LF, PA.MF, PA.RF, PA.LP, PA.RP, PA.MO). In summary, in this study, objective response to cybersickness was confirmed through 128 channels of EEG. The analysis results showed that there was a clearly distinguished reaction at a specific part of the brain. Using the results and analytical methods of this study, it is expected that it will be useful for the future studies related to the cybersickness.

키워드

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