Detecting Heart Rate from Virtual Reality Headset-Embedded Inertial Sensors: A Kinetic Energy Approach

At each cardiac beat, blood flowing through the arterial tree produces micro-movements that can be measured by positioning inertial sensors in contact with the body. The resulting signal is the ballistocardiogram (BCG). The study aims to demonstrate the feasibility to exploit inertial sensors embedded in a virtual reality (VR) headset to estimate heart rate (HR). Eight volunteers were enrolled. 1-minute head BCG signals were acquired in supine, sitting and standing position using the tri-axial accelerometer and gyroscope (fs=71[71;77] Hz) integrated in a Oculus Quest (Facebook) VR headset. Linear and rotational kinetic energies were computed and used to automatically detect cardiac beats. Inter-beat intervals were extracted and mean HR was computed. In addition, 1-lead ECG signal was acquired and used as a gold standard for HR measurement. The HR values computed from BCG in each posture were compared with the gold standard (Wilcoxon Signed Rank Test, p< 0.05). Correlation (r2) and Bland Altman analyses were also performed. Best results were obtained using the rotational kinetic energy derived by the gyroscope, obtaining HRs comparable to the gold standard in both supine and sitting postures, with high correlation, no bias, and acceptable limits of agreement. In standing posture, the balancing movements for body equilibrium maintenance contributed reducing HR estimate accuracy. This is the first study in which HR has been measured using kinetic energy computed from the head-BCG obtained with a commercial VR headset, providing important insights on the possibility to expand the use of inertial units to accurately and non-invasively monitor physiological parameters.