Blood pressure (BP) monitoring is an important tool for management of hypertension, which is a significant risk for cardiovascular disease and premature death. Since cuff-based BP measurement can be uncomfortable and does not provide continuous readings, several cuffless methods that are typically based on within-beat information or on the pulse transit time (PTT) have recently been investigated. This work proposes a novel cuffless BP estimation approach that mainly uses the information from cardiovascular dynamics of photoplethysmogram (PPG) waveforms. This work is divided into three parts. The first part proposes a calibration-free approach that uses dynamic changes in the pulse waveform. Results from 200 patients showed that the method achieved grade B, in terms of accuracy, for diastolic blood pressure (DBP) based on the British Hypertension Society (BHS) standard and complied with the accuracy requirements of the Association for Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization (AAMI/ESH/ISO) standard. The second part presents a method based on calibrated cardiovascular dynamics, achieved through a mathematical model that relates reflective PTT (R-PTT) to BP. Results from 30 patients showed a mean error (ME) of 0.58 mmHg, standard deviation of the error (SDE) of 8.13 mmHg, and a mean absolute error (MAE) of 4.93 mmHg for DBP and an ME of 2.52 mmHg, SDE of 12.28 mmHg, and an MAE of 8.82 mmHg for systolic blood pressure (SBP). The third part proposes a calibration-free method that combines morphology features and dynamic changes of the pulse waveform over short intervals. In this method a neural network was trained on 200 patients and tested on never-seen data from 25 other patients and provided an ME of -0.31 mmHg, SDE of 4.89 mmHg, and MAE of 3.32 mmHg for DBP and an ME of -4.02 mmHg, SDE of 10.40 mmHg, and MAE of 7.41 mmHg for SBP. Overall, the results show that cardiovascular dynamics may contribute useful information for cuffless estimation of BP.

This research presents a pulse-by-pulse analysis of Oscillometric blood pressure waveform at systolic, diastolic and mean arterial pressure points. Using a mathematical optimization technique, pulses are characterized into component harmonic by minimizing the least square error. The results at the important pressure points are analyzed and compared for different subject using different waveform extraction techniques. Blood pressure is estimated using the harmonic parameters. The approach studies changes in the parameters as oscillometric blood pressure recording is done. 8 harmonic parameters are obtained from the pulse characterization and are used to estimate Systolic arterial Blood Pressure, Mean arterial Blood Pressure, and Diastolic arterial Blood Pressure. The estimates are compared with our reference value to determine which has the best agreement. The proposed method is further compared with Maximum Amplitude Algorithm and Pulse Morphology Algorithm. The effect of oscillometric waveform extraction methods on the proposed method is observed. The experiment established the fact that the extraction technique can alter the shape of oscillometric pulses. The methods were compared and it was observed that the used extraction methods did not make any significant difference on the accuracy, using this technique.