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

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 compu...

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Vydané v:	Bioengineering (Basel) Ročník 12; číslo 2; s. 131
Hlavní autori:	Lee, Soojeong, Al-antari, Mugahed A., Joshi, Gyanendra Prasad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.02.2025 MDPI
Predmet:	Algorithms Blood pressure Confidence intervals cuff-less blood-pressure estimation Decisions Electrocardiography Estimates Exercise Gaussian process Gaussian processes regression gradient boosting algorithm Hypertension Measurement Monitoring systems Neighborhoods Neural networks Physiology Statistical analysis Uncertainty gradient boosting algorithm Gaussian processes regression confidence intervals uncertainty cuff-less blood-pressure estimation
ISSN:	2306-5354, 2306-5354
On-line prístup:	Získať plný text
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