Optimizing Earbud-Based Ballistocardiogram: A Comparative Study of Calibration, PCA, and Axis Fusion

The earbud-based ballistocardiogram (BCG) holds significant promise for monitoring diverse physiological signals, including stress, cardiac activity, and blood pressure. However, unlike traditional methods that measure the force component along the body longitudinal axis (head to foot) for enhanced BCG signal quality, ear-worn devices are prone to orientation misalignment, leading to significant variations in BCG morphology. To address this challenge, this paper investigates various axis selection techniques for enhancing earbud BCG, including thresholding-based axis selection, principal component analysis (PCA), and sensor-to-segment calibration. We systematically compare these approaches to the widely adopted baseline method, which utilizes the default axis that is most closely aligned with the longitudinal axis during wear. Our analysis focuses on evaluating the heart rate variability (HRV) and morphological features derived from BCG. Through a comprehensive investigation, we aim to identify optimal strategies for obtaining high-quality BCG signals using ear-worn devices.