# Improved Confidence-Interval Estimations Using Uncertainty Measure and Weighted Feature Decisions for Cuff-Less Blood-Pressure Measurements

## TL;DR

This paper introduces a method to improve confidence intervals for cuff-less blood pressure measurements using uncertainty measures and weighted features.

## Contribution

A novel method combining Gaussian process regression and gradient boosting for accurate cuff-less BP estimation with improved confidence intervals.

## Key findings

- The proposed method achieved a mean error standard deviation of 2.94 mmHg for systolic and 1.50 mmHg for diastolic blood pressure.
- Weighted feature decisions combined with GPR and GBA reduced mean absolute error to 1.46 mmHg for systolic and 0.69 mmHg for diastolic blood pressure.
- BP estimates were confirmed to be within the confidence intervals for almost all test subjects.

## Abstract

This paper presents a method to improve confidence-interval (CI) estimation using individual uncertainty measures and weighted feature decisions for cuff-less blood-pressure (BP) measurement. We obtained uncertainty using Gaussian process regression (GPR). The CI obtained from the GPR model is computed using the distribution of BP estimates, which provides relatively wide CIs. Thus, we proposed a method to obtain improved CIs for individual subjects by applying bootstrap and uncertainty methods using the cuff-less BP estimates of each subject obtained through GPR. This study also introduced a novel method to estimate cuff-less BP with high fidelity by determining highly weighted features using weighted feature decisions. The standard deviation of the proposed method’s mean error is 2.94 mmHg and 1.50 mmHg for systolic blood pressure (SBP) and (DBP), respectively. The mean absolute error results were obtained by weighted feature determination combining GPR and gradient boosting algorithms (GBA) for SBP (1.46 mmHg) and DBP (0.69 mmHg). The study confirmed that the BP estimates were within the CI based on the test samples of almost all subjects. The weighted feature decisions combining GPR and GBA were more accurate and reliable for cuff-less BP estimation.