Comparison of ECG-Free Algorithms for Heart Rate Computation From Head-BCG Signals Obtained With Smart Eyewear

Ballistocardiography (BCG) is a non-invasive method to assess cardiac activity by detecting body recoil in response to heart contractions and blood flow. Traditionally, BCG technology was bulky, but advances in microelectromechanical sensors (MEMS) made it portable. MEMS, when placed on the head, can detect micro-vibrations caused by blood movement, defined as Head-BCG (HBCG). This study aimed to measure heart rate (HR) using MEMS embedded in smart eyewear, comparing different methods to compute HR without the reference ECG. Twenty subjects wore an eyewear embedded with a 3-axial accelerometer and gyroscope, from which 6D HBCG signals were recorded. A 1-lead ECG was simultaneously acquired as gold standard. HR was calculated from the HBCG using the Fast Fourier Transform and the template matching method, applied both on the MEMS signals and on the linear and rotational kinetic energy. Template matching showed high accuracy in beats identification, especially when applied on accelerometer signals (up to 83%). In conclusion, MEMS in smart eyewear can accurately measure HR, paving the way for the possible utilization of such wearable technology for unobtrusive daily monitoring of cardiac activity.