Impact of Virtual Reality Immersion on User Engagement and Performance During Gamified Respiratory Muscle Training

Abstract

Inspiratory Muscle Training (IMT) is a well-established intervention for enhancing respiratory strength; however, its clinical efficacy is frequently compromised by low adherence and high dropout rates due to the repetitive nature of traditional protocols. While screen-based gamified biofeedback is the most common digital training approach, these non-immersive (NI) conditions often lead to split attention and lack the controlled, private environments necessary for optimal engagement and exercise quality. This study evaluated the impact of immersion level on respiratory performance and user experience by comparing two conditions in gamified Virtual Reality (VR) environments: fully immersive (FI) and NI. The IMT was performed using an instrumented threshold load device, where real-time mouth pressure drove gamified environments designed to guide respiratory patterns. The results demonstrate that perceived effort and fatigue remained consistent across immersion levels; however, the FI condition provided a higher level of immersion despite a reported reduction in breathing control. Notably, 73% of participants found the FI condition more motivating, with higher scores in focus (60%), user preference (63%), and efficacy (40%). Crucially, increased task complexity widened the performance gap between immersion levels. In scenarios requiring higher respiratory muscle workload, significant differences emerged in breathing regulation, specifically regarding the inspiratory duty cycle, favoring the NI condition. Specifically, the NI condition exhibited a higher inspiratory duty cycle and higher scores compared to the FI condition. These findings suggest that while FI significantly boosts user motivation, the synergy between the head-mounted display (HMD) and the physical demands of the threshold device may disrupt respiratory regulation during high-effort tasks. This highlights a critical design trade-off between immersion levels and physiological precision that must be addressed in the development of future digital pulmonary interventions.