Spectral Parametrization of PPG, IPG and pAT Pulse Waves for Continuous Noninvasive Blood Pressure Estimation

Recent technological advances are enabling the sector of wearables to rapidly expand. An increasingly big emphasis is placed on introducing continuous monitoring of biosignals such as heart rate, SpO2 and ECG. Extrapolating from the current trend of making clinical signals available to the general public, arterial blood pressure is a realistic and useful next step. Its robust, non-obtrusive, continuous acquisition is of great interest and importance, especially in clinical settings. Using a body sensor network, we acquire photoplethysmography, bioimpedance and pulse applanation tonometry signals synchronously at the periphery. The pulse waves are decomposed into spectral amplitude and phase. The values thereof are then used as features for blood pressure estimation. We apply a polynomial regression method and evaluate performance employing leave one out cross validation. A single initial parameter calibration is applied for the entire measurement. Our results with noisy datasets exhibit acceptable tracking of mean arterial pressure, with a baseline error of 0.62 mmHg, absolute error of 4.6 mmHg and standard deviation of 5.3 mmHg. Spectral phase information mostly outperforms amplitude information. Optically, electrically and electro-mechanically derived signals perform similarly, but best compliance and quality is achieved for electrical bioimpedance. We conclude that using a single, peripherally acquired plethysmographic waveform for blood pressure tracking is feasible, offering increased placement flexibility and compliance at the cost of reduced accuracy.