Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

被引:15
作者
Barathi, Soumya C. [1 ]
Proulx, Michael [1 ]
O'Neill, Eamonn [1 ]
Lutteroth, Christof [1 ]
机构
[1] Univ Bath, REal & Virtual Environm Augmentat Labs REVEAL, Bath, Avon, England
来源
PROCEEDINGS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'20) | 2020年
基金
英国工程与自然科学研究理事会;
关键词
VR exergaming; affect recognition; psychophysiological correlates; high intensity exercise; INTRINSIC MOTIVATION; PHYSICAL-ACTIVITY; INDIVIDUAL-DIFFERENCES; SPORT PARTICIPATION; OPTIMAL EXPERIENCE; EYE-MOVEMENTS; PUPIL SIZE; EXERCISE; MUSIC; PERFORMANCE;
D O I
10.1145/3313831.3376596
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
User experience estimation of VR exergame players by recognising their affective state could enable us to personalise and optimise their experience. Affect recognition based on psychophysiological measurements has been successful for moderate intensity activities. High intensity VR exergames pose challenges as the effects of exercise and VR headsets interfere with those measurements. We present two experiments that investigate the use of different sensors for affect recognition in a VR exergame. The first experiment compares the impact of physical exertion and gamification on psychophysiological measurements during rest, conventional exercise, VR exergaming, and sedentary VR gaming. The second experiment compares underwhelming, overwhelming and optimal VR exergaming scenarios. We identify gaze fixations, eye blinks, pupil diameter and skin conductivity as psychophysiological measures suitable for affect recognition in VR exergaming and analyse their utility in determining affective valence and arousal. Our findings provide guidelines for researchers of affective VR exergames.
引用
收藏
页数:15
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