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Engagement classification algorithm based on ECG(electrocardiogram) response in competition and cooperation games

심전도 반응 기반 경쟁, 협동 게임 참여자의 몰입 판단 알고리즘 개발

  • Lee, Jung-Nyun (Dept. of Emotion Engineering, Sangmyung University) ;
  • Whang, Min-Cheol (Dept. of Intelligent Engineering Informatics for Human, Sangmyung University) ;
  • Park, Sang-In (Industry-Academy Cooperation Team, Sangmyung University) ;
  • Hwang, Sung-Teac (Dept. of Emotion Engineering, Sangmyung University)
  • 이정년 (상명대학교 감성공학과) ;
  • 황민철 (상명대학교 휴먼지능정보공학과) ;
  • 박상인 (상명대학교 서울산학협력단) ;
  • 황성택 (상명대학교 감성공학과)
  • Received : 2017.03.13
  • Accepted : 2017.04.20
  • Published : 2017.04.20

Abstract

Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

최근 청소년들의 인터넷 및 스마트폰 과도한 사용이 사회적 이슈가 되어왔다. 작업에 대한 몰입 수준은 좋은 결과물을 만들 수 있는 긍정적 효과와 과 몰입 같은 부정적 효과를 모두 가지고 있다. 본 연구는 심혈관 반응 기반의 몰입 상태를 판단하는 알고리즘을 개발하고자 하였다. 피험자들은 무 자극 상태, 그리고 몰입을 유발하기 위한 패턴 맞추기 게임을 수행하였고, 몰입 수준을 제공하기 위해 협력과 경쟁 태스크로 나누어 실험 디자인 하였다. 각 태스크에 따라 심박과 진폭의 상관성을 분석하고 다항식 회귀 분석을 통해 회귀식 및 정확도를 확인하였다. 결과는 게임 태스크일 때, 심박과 진폭은 양의 상관성을 보였으며 무자극일 때 음의 상관성을 보였다. 개발된 다차항 회귀식으로 게임 태스크와 무 자극을 구분하는 정확도는 평균 89%의 정확도를 보였다. 태스크간의 차이는 76.5% 정확도를 확인하였다. 본 연구는 실시간으로 몰입 수준을 정량적으로 평가하는데 사용될 수 있을 것으로 기대된다.

Keywords

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