Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

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.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992 </p

Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame

Participating in competitive races can be a thrilling experience for athletes, involving a rush of excitement and sensations of flow, achievement, and self-fulfilment. However, for non-athletes, the prospect of competition is often a scary one which affects intrinsic motivation negatively, especially for less fit, less competitive individuals. We propose a novel method making the positive racing experience accessible to non-athletes using a high-intensity cycling VR exergame: by recording and replaying all their previous gameplay sessions simultaneously, including a projected future performance, players can race against a crowd of "ghost" avatars representing their individual fitness journey. The experience stays relevant and exciting as every race adds a new competitor. A longitudinal study over four weeks and a cross-sectional study found that the new method improves physical performance, intrinsic motivation, and flow compared to a non-competitive exergame. Additionally, the longitudinal study provides insights into the longer-term effects of VR exergames

Interactive Feedforward for Improving Performance and Maintaining Intrinsic Motivation in VR Exergaming

Exergames commonly use low to moderate intensity exercise protocols. Their effectiveness in implementing high intensity protocols remains uncertain. We propose a method for improving performance while maintaining intrinsic motivation in high intensity VR exergaming. Our method is based on an interactive adaptation of the feedforward method: a psychophysical training technique achieving rapid improvement in performance by exposing participants to self models showing previously unachieved performance levels. We evaluated our method in a cycling-based exergame. Participants competed against (i) a self model which represented their previous speed; (ii) a self model representing their previous speed but increased resistance therefore requiring higher performance to keep up; or (iii) a virtual competitor at the same two levels of performance. We varied participants' awareness of these differences. Interactive feedforward led to improved performance while maintaining intrinsic motivation even when participants were aware of the interventions, and was superior to competing against a virtual competitor