As the awareness of maintaining health continues to rise, there is an increasing demand for advanced, convenient, and non-intrusive health monitoring solutions. Given the rapid advancements in and wide-spread adoption of virtual reality (VR) technology and devices, this paper introduces a contactless heart rate estimation and user identity recognition system specifically designed for real-world VR environments. We propose a video-based heart rate estimation model that utilizes remote photoplethysmography (rPPG) to reconstruct blood volume pulse (BVP). The rPPG signals are generated from the video recordings captured by the eye infrared cameras used for eye tracking in VR headset. Additionally, we investigate the potential application of the reconstructed rPPG signals in user identification tasks. The experiments are conducted using a self-constructed dataset, which comprises binocular video and fingertip photoplethysmography (PPG) signals captured from 11 participants while they naturally wore VR headsets. The results substantiate the feasibility of the proposed system in enabling unobtrusive heart-rate estimation and identity recognition within immersive virtual environments.