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This paper presents an analysis of the common problems in identifying the key points of pulse wave. For the processing of synchronous recorded pulse wave and electrocardiogram signals a software module has been developed in MATLAB program. This module provides displaying of the signals, key points detection, pulse wave transit time calculation and evaluation of the variability of this parameter. For estimation of the characteristic form of the pulse wave an averaged model of several neighbor cardiac cycles depending on reference point is developed. The model allows visually evaluating the shape of the pulse wave and determining the average parameters values for the selected segment. To assess the variability of pulse wave shape overlapping could be implemented.

Systolic blood pressure (SBP) is one of the important vital signs that need to be monitored for personal healthcare. Measuring SBP via pulse wave transit time (PWTT) requires monitoring ECG and pulse wave signals simultaneously, which has no portability. And before the measurement the parameters indicating the relationship between BP and PWTT must be calculated through training. This paper describes a portable method developed by the authors to measure SBP from PWTT using one Android smart phone. Volume pulse waves were acquired by a smart phone with its built-in camera, and then accelerated pulse waves were gotten through filtering, amplifying and processing the signals. The PWTT between the progressive and reflected waves of the accelerated pulse waves was calculated. The tester swayed his arm with hand holding the same phone to change the SBP for the training. The displacement of the hand was calculated through the accelerometer of the smart phone. Experimental results indicated that there is no obvious difference between SBP measured by the new system and by an electronic sphygmomanometer with error less than 10mmHg.

A new technology called estimated continuous cardiac output (esCCO) uses pulse wave transit time (PWTT) obtained from an electrocardiogram and pulse oximeter to measure cardiac output (CO) non-invasively and continuously. This study was performed to evaluate the accuracy of esCCO during exercise testing. We compared esCCO with CO measured by the echo Doppler aortic velocity-time integral (VTIao_CO). The correlation coefficient between esCCO and VTIao_CO was r= 0.87 (n= 72). Bias and precision were 0.33 ± 0.95 L/min and percentage error was 31%. The esCCO could detect change in VTIao_CO larger than 1 L/min with a concordance rate of 88%. In polar plot, 83% of data are within 0.5 L/min, and 100% of data are within 1 L/min. Those results show the acceptable accuracy and trend ability of esCCO. Change in pre-ejection period (PEP) measured by using M-mode of Diagnostic Ultrasound System accounted for approximately half of change in PWTT. This indicates that PEP included in PWTT has an impact on the accuracy of esCCO measurement. In this study, the validity of esCCO during exercise testing was assessed and shown to be acceptable. The result of this study suggests that we can expand its application.

Blood pressure is one of important parameter in assessing patients' health status. The measurement of blood pressure using conventional method is less practical in monitoring continuous blood pressure. This paper proposed an automatic technique for monitoring blood pressure continuously using the relation of pulse wave transit time (PWTT) with systolic blood pressure (SBP). The measurement of PWTT involves the marking of electrocardiograph R (ECG-R) peak from electrocardiograph (ECG) signal and the peak of peripheral pulse wave from photoplethysmography (PPG) signal. Data collection involves three different sessions, which are resting period, exercise period and recovery period, thus establishing the relationship between SBP and PWTT. The results of monitoring blood pressure based on pulse wave transit time will facilitate personal healthcare monitoring blood pressure continuously.

In order to know the effect of the change in the pre-ejection period (PEP) included in the pulse wave transit time (PWTT), PWTT of the toe, finger and nose was measured in a clinical situation and the difference between each site's PWTT was calculated in order to eliminate the PEP. The slope of PWTT against systolic blood pressure (SBP) after administration of ephedrine and phenylephrine was calculated. The result suggested that because change in PEP caused inconsistency of the relationship between PWTT and blood pressure (BP), PEP had less effect on the toe PWTT than on the PWTT of other sites.