Performance and User Experience Studies of HILLES: Home-based Immersive Lower Limb Exergame System

Abstract

Head-Mounted Devices (HMDs) have become popular for home-based immersive gaming. However, using lower limb motion in the immersive virtual environment is still restricted. This work introduces an RGB-D camera-based motion capture system alongside a standalone HMD for Home-based Immersive Lower Limbs Exergame Systems (HILLES) in a seated pose. With the advance of neural network models, camera-based 3D body tracking accuracy is increasing. Nevertheless, the high demand for computing resources on model inference may compromise the game engine's performance. Accordingly, HILLES applies a distributed architecture to leverage the resources effectively. The system performances, such as frames per second and latency, are compared with a centralized system. For an immersive exergame, a pet walking around could raise safety issues. Hence, we also showcase that the camera system can provide an additional safety feature by combining an object detection model. Besides, another challenge in games focusing on lower limb interactions is the safe reachability of different virtual objects from a seated pose. Accordingly, in the user study, a stomping game with two reachability enhancements, including leg extension and seated navigation, is implemented based on the HILLES to evaluate and explore the gaming experience. The result shows that the system motivates the leg exercise, and the added enhancements may adjust the game difficulty. However, the enhancements may also distract users from focusing on leg exertion. The derived insight could benefit the lower limb exergame design in the future.