Towards Real-Time Recognition of Users’ Mental Workload Using Integrated Physiological Sensors Into a VR HMD
This paper describes an ``all-in-one'' solution for the real-time recognition of users' mental workloads in VR through the customization of a commercial HMD with physiological sensors. We conducted an extensive user study (N = 75) to collect mental workload data. The classification accuracy of 4 levels of mental workload using sensors embedded in the HMD is compared to the classification performance using commercial grade systems. In addition, we discuss the role of the signal normalization procedures and the contribution of the different physiological signals on the recognition accuracy.
Nov 6, 2020
