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Regulation and inhibition of high blood pressure, known as hypertension are intricate, and it demands a continuous, accurate blood pressure measurement system. All the existing continuous non-invasive techniques own challenges such as exact placement of the sensor, reconstruction of arterial pressure from finger cuff, frequent and subject based calibration. This paper presents an algorithm based on new time-domain features for continuous blood pressure monitoring which is crucial in intensive care units and can be used to predict cardiovascular ailments.

Here, we propose the method to estimate BP that extracts informative features like Womersley number (α), QRS, QTc interval, SDI from ECG and PPG signals and regression techniques which are employed to estimate blood pressure continuously. Performance metrics like MAE, RMSE, r, bias & 95% CI are considered to validate the …