Abstract

Blood pressure (BP) measurement plays an essential role in the prevention of cardiovascular diseases. Studies have demonstrated Ultrasound (US) based BP analysis method combining with peripheral components of the circulatory system. In this paper, a cuffless BP measurement technique has been proposed using a portable continuous wave Doppler US system which consumes < 4 Watt of power. The US blood flow signal acquired utilizing 8 MHz pencil transducer probe from the brachial artery is denoised using soft thresholding method. The spectrogram envelope of maximum frequency is obtained by an adaptive signal noise slope intersection (SNSI) method to extract hemodynamic features. In the proposed method, 2-element Windkessel (WK) model consisting of peripheral resistance and arterial compliance is employed for BP estimation. Based on the extracted features, a machine learning algorithm determines the WK model parameters. From the experiments conducted on 85 subjects, it has been observed that both systolic and diastolic BP achieve Grade B and Grade C for British Hypertension Society (BHS) and IEEE Std. 1708 protocols, respectively. Regarding Association for the Advancement of Medical Instrumentation (AAMI) standard, diastolic BP estimation error is within an acceptable limit. The robustness of the approach is examined using pre-exercise and post-exercise performance of 10 subjects. Moreover, the effect on arterial compliance for increased BP and aging is observed to characterize the dynamic property of arterial system. The proposed method is non-invasive, non-occlusive, independent of any additional interfaces, operates with a small dataset and worthy of implementation as a portable system for point-of-care application.

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