Interactive Feedforward for Improving Performance and Maintaining Intrinsic Motivation in VR Exergaming (CHI 2018)
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.