Optimizing Sensor Placement and Wavelength Selection for Head-Mounted Photoplethysmography in Wearable Applications

Abstract

Measuring heart rate (HR) and HR variability (HRV) is critical for assessing the cognitive load in wearable health monitoring and extended reality applications. Realizing the continuous measurement of these parameters requires hands-free sensing solutions that minimize interference with daily activities. The aim of this study is to identify the best configuration of anatomical location on the head and wavelength for making accurate measurements of HR and HRV using a noninvasive photoplethysmography (PPG) sensor, while the wearer is at rest or during walking. To identify the optimal placement, we analytically compared three head locations (temple, supraorbital, and glabella) combined with three wavelengths [red, infrared (IR), and green] and validated the results against an electrocardiography (ECG) reference. We recorded data for 16 participants during 5-min sessions under both static and walking conditions. Temple–IR achieved clinical-grade accuracy for HR during static conditions (5.5% error), whereas glabella–IR produced the most accurate results during walking. Notably, the performance of the three wavelengths converged during motion, as the static advantage of IR disappeared. Head-mounted PPG demonstrated statistical equivalence to finger sensors across both conditions. Choice of sensor location depends on activity, with no single site being optimal across both conditions. These findings indicate that multisensor PPG configurations with motion compensation are necessary for robust head-mounted cardiovascular monitoring.