Using accelerometry and heart rate data for real-time monitoring of soldiers’ stress in a dynamic military virtual reality scenario

Real-time physiological stress monitoring would be a relevant addition to virtual reality (VR) training for high-risk professions, such as the military. VR is highly suitable for the implementation of such monitoring due to the controlled environment and the already used wearables. However, physiological stress measurements suffer from distortion due to physical activity. Therefore, we tested whether we can use accelerometry to correct non-invasively measured heart rate (HR) for physical activity in 23 soldiers who performed three room-clearing VR scenarios. These scenarios were dynamic, in that soldiers moved around in the VR environment by walking around in the real environment. In contrast to uncorrected HR, and HR corrected by subtracting baseline HR measured when walking, the accelerometry-corrected HR was able to significantly predict the participants’ self-reported stress in the scenarios, p = 0.047, R ² = 0.11. Whereas uncorrected HR significantly predicted self-reported physical demand, p = 0.028, R ² = 0.09, the accelerometry-corrected HR did not. All HR measures significantly predicted self-reported mental effort, which was most strongly the case for uncorrected HR, p < 0.001 R ² = 0.42. These findings, in combination with the methods’ low sensitivity to motion artifacts and non-invasiveness, are very promising for its use to monitor stress in real-time during dynamic VR training scenarios.