O18 UNCERTAINTY QUANTIFICATION OF WEARABLE CUFFLESS BLOOD PRESSURE MEASUREMENT

Background and Objective: Due to aleatoric and epistemic uncertainty, most cuffless blood pressure (BP) estimation models struggle to provide reliable and accurate BP estimations. The purpose of this study is to quantify the uncertainty of wearable cuffless BP estimation so as to reduce the impact of uncertainty on the accuracy of model estimation, and in the meanwhile to provide an estimated uncertainty interval (UI) in addition to the point estimation. Methods: We developed a gradient boosting regression tree (GBRT) model to estimate ambulatory BP and the estimation UI with eight noninvasive features extracted from wearable photoplethysmogram (PPG) and electrocardiogram (ECG) signals. We validated the proposed method with the Microsoft Aurora dataset that was originally collected for the Aurora-BP study. We identified 483 subjects (247 males) with wearable watches collecting PPG, ECG, and other signals, while ambulatory BP was monitored hourly using an oscillometric BP device. We trained the model with quantile loss on 60% of subjects (2954 samples), then calibrated the estimated UI with conformal predication with 24% (2148 samples) of subjects and tested the model with 16% (1658 samples) of the subjects. Results: The mean absolute difference (MAD) in systolic BP (SBP) and diastolic BP (DBP) estimated by the GBRT model were 13.96 mmHg and 9.89 mmHg, respectively. Then, with implementation of conformal prediction with error rates of ϵ=0.05, for the test set samples, the percentage of the estimated UI covering the reference BP during the daytime and nighttime phases can reach 91.67% and 95.89%, respectively. Conclusions: The combination of the GBRT model with conformal predication can quantify the uncertainty in cuffless BP estimations. In addition, the estimated uncertainty quantification interval together with the point estimation is potentially more reliable than single-point estimation, which could benefit better diagnosis and treatment of hypertension.