Comparative study on the accuracy of a cuffless continuous blood pressure measurement device based on photoplethysmography and deep learning algorithm
[Objective]To test the accuracy of a cuffless continuous blood pressure measurement(CBPM)device based on photoplethysmography(PPG)and deep learning algorithms in healthy people.[Methods]24-hour ambulatory blood pressure monitoring(ABPM)was performed on healthy adult subjects with certified equipment,and CBPM based on PPG and deep learning algorithm was used at the same time.Paired t test,correlation analysis,and Bland-Altman plots were used to assess the consistency between devices,including mean comparisons at the same time point(point-to-point)and night time periods(period-to-period).[Results]A total of 36 subjects with valid blood pressure data were obtained.In the point-to-point analysis,the mean values of systolic blood pressure(SBP)and diastolic blood pressure(DBP)in the CBPM group and the ABPM group were 1.22±8.30 mmHg and 1.61±9.27 mmHg,respectively,and the paired t test showed that there was no significant statistical difference between the two groups(P＞0.05).Pearson correlation analysis showed that the measured values of SBP(r=0.670,P＜0.001)and DBP(r=0.503,P＜0.001)were significantly correlated between the two groups at the same time point.In the period-to-period analysis,the mean values of SBP(117.15±14.30 mmHg and 114.73±13.35 mmHg,P＞0.05)and DBP(73.50±11.70 mmHg and 69.96±9.64 mmHg,P＞0.05)were not statistically different between the two groups during the night time period.[Conclusion]The CBPM device based on PPG and deep learning algorithm provides continuous blood pressure measurements comparable to ABPM,and is useful for daily blood pressure monitoring and blood pressure variability in the future analysis to provide new tools for the prevention and management of hypertension.
万方数据
维普
