In order to improve the accuracy of blood pressure measurement in wearable devices, this paper presents a method for detecting blood pressure based on multiple parameters of pulse wave. Based on regression analysis between blood pressure and the characteristic parameters of pulse wave, such as the pulse wave transit time (PWTT), cardiac output, coefficient of pulse wave, the average slope of the ascending branch, heart rate, etc. we established a model to calculate blood pressure. For overcoming the application deficiencies caused by measuring ECG in wearable device, such as replacing electrodes and ECG lead sets which are not convenient, we calculated the PWTT with heart sound as reference (PWTT(PCG)). We experimentally verified the detection of blood pressure based on PWTT(PCG) and based on multiple parameters of pulse wave. The experiment results showed that it was feasible to calculate the PWTT from PWTT(PCG). The mean measurement error of the systolic and diastolic blood pressure calculated by the model based on multiple parameters of pulse wave is 1.62 mm Hg and 1.12 mm Hg, increased by 57% and 53% compared to those of the model based on simple parameter. This method has more measurement accuracy.
Blood Pressure ; Blood Pressure Monitoring, Ambulatory ; Cardiac Output ; Electrocardiography ; Heart Rate ; Heart Sounds ; Humans ; Pulse Wave Analysis ; Regression Analysis