Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert–Huang transform

It is widely accepted that pulse transit time (PTT), from the R wave peak of electrocardiogram (ECG) to a characteristic point of photoplethysmogram (PPG), is related to arterial stiffness, and can be used to estimate blood pressure. A promising signal processing technology, Hilbert–Huang transform (HHT), is introduced to analyze both ECG and PPG data, which are inherently nonlinear and non-stationary. The relationship between blood pressure and PTT is illustrated, and the problems of calibration and re-calibration are also discussed in this paper. Moreover, multi-innovation recursive least square algorithm is employed to update the unknown parameter vector for the model and improve the results. Our algorithm is tested based on the continuous data from MIMIC database, and the accuracy is calculated to validate the proposed method.

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► Non-invasive cuff-less blood pressure estimations are in need.
► Pulse transit time between electrocardiogram and photoplethysmogram is used.
► Hilbert–Huang transform is applied considering nonlinearity and non-stationarity.
► Multi-innovation recursive least square algorithm is tested with various recalibration periods.