Papers Blood pressure estimation
“Blood pressure estimation” 태그가 달린 논문 41편 · 필터 해제
Change Point--Aware Evaluation and Re-Calibration of PPG-Based Blood Pressure Estimation
Non-invasive continuous blood pressure (BP) monitoring using photoplethysmography (PPG) is a promising alternative to cuff-based measurements. However, existing PPG-based BP estimation studies predominantly rely on aggre…
Blood pressure estimationChange Point DetectionSingle-Beat Cuffless Blood Pressure Estimation Using Ear-PPG and ECG with a Lightweight Hybrid Learning Framework
Continuous cuffless blood pressure (BP) monitoring remains challenging due to motion artifacts, physiological variability, and the limited robustness of conventional pulse transit time (PTT) models under dynamic conditio…
Blood pressure estimationBlood Pressure Estimation from PPG: A Comparative Study of Direct and ECG-Mediated Deep Learning Pipelines
Continuous cuffless blood pressure (BP) monitoring is essential for connected health systems and wearable devices, enabling early detection, longitudinal tracking, and personalized management of cardiovascular disease. M…
Blood pressure estimationDMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals
Blood pressure (BP) is a key marker for cardiovascular risk assessment and therapeutic decision-making, and Photoplethysmography (PPG) enables low-cost, wearable-friendly cuffless BP estimation. However, even with recent…
Blood pressure estimationRepresentation LearningUncertainty Reliability Under Domain Shift: An Investigation for Data-Driven Blood Pressure Estimation in Photoplethysmography
Uncertainty quantification (UQ) is critical for safety-critical domains like healthcare, yet it is rarely evaluated under realistic out-of-distribution (OOD) conditions. Here, we assessed predictive performance and uncer…
Blood pressure estimationAttractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography
This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure (BP) information sufficient for AAMI-standard estimation, and validate…
Blood pressure estimationEnd-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables
Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, fully on-board processing is desirable to ensure user data confidenti…
Neural Architecture SearchBlood pressure estimationBenchmarking and Enhancing PPG-Based Cuffless Blood Pressure Estimation Methods
Cuffless blood pressure screening based on easily acquired photoplethysmography (PPG) signals offers a practical pathway toward scalable cardiovascular health assessment. Despite rapid progress, existing PPG-based blood …
Blood pressure estimationPMB-NN: Physiology-Centred Hybrid AI for Personalized Hemodynamic Monitoring from Photoplethysmography
Continuous monitoring of blood pressure (BP) and hemodynamic parameters such as peripheral resistance (R) and arterial compliance (C) are critical for early vascular dysfunction detection. While photoplethysmography (PPG…
Blood pressure estimationCuffless Blood Pressure Estimation from Six Wearable Sensor Modalities in Multi-Motion-State Scenarios
Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, and sustained hypertension is an often silent risk factor, making cuffless continuous blood pressure (BP) monitoring with wearable dev…
Blood pressure estimationContrastive LearningVision4PPG: Emergent PPG Analysis Capability of Vision Foundation Models for Vital Signs like Blood Pressure
Photoplethysmography (PPG) sensor in wearable and clinical devices provides valuable physiological insights in a non-invasive and real-time fashion. Specialized Foundation Models (FM) or repurposed time-series FMs are us…
parameter-efficient fine-tuningBlood pressure estimationGeneralizable Blood Pressure Estimation from Multi-Wavelength PPG Using Curriculum-Adversarial Learning
Accurate and generalizable blood pressure (BP) estimation is vital for the early detection and management of cardiovascular diseases. In this study, we enforce subject-level data splitting on a public multi-wavelength ph…
Blood pressure estimationDomain Knowledge Integrated CNN-xLSTM-xAtt Network with Multi Stream Feature Fusion for Cuffless Blood Pressure Estimation from Photoplethysmography Signals
Estimating blood pressure (BP) from photoplethysmography (PPG) signals is challenging due to signal variability and noise, as well as the complex relationship between PPG and BP, which requires sophisticated algorithms a…
Blood pressure estimationPhotoplethysmography (PPG)A Dataset and Toolkit for Multiparameter Cardiovascular Physiology Sensing on Rings
Smart rings offer a convenient way to continuously and unobtrusively monitor cardiovascular physiological signals. However, a gap remains between the ring hardware and reliable methods for estimating cardiovascular param…
Blood pressure estimationGeneralizable deep learning for photoplethysmography-based blood pressure estimation -- A Benchmarking Study
Photoplethysmography (PPG)-based blood pressure (BP) estimation represents a promising alternative to cuff-based BP measurements. Recently, an increasing number of deep learning models have been proposed to infer BP from…
BenchmarkingBlood pressure estimationDomain AdaptationOut-of-Distribution Generalization+1Finetuning and Quantization of EEG-Based Foundational BioSignal Models on ECG and PPG Data for Blood Pressure Estimation
Blood pressure (BP) is a key indicator of cardiovascular health. As hypertension remains a global cause of morbidity and mortality, accurate, continuous, and non-invasive BP monitoring is therefore of paramount importanc…
Blood pressure estimationEEGElectrocardiography (ECG)Photoplethysmography (PPG)+1Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables
PPG-based Blood Pressure (BP) estimation is a challenging biosignal processing task for low-power devices such as wearables. State-of-the-art Deep Neural Networks (DNNs) trained for this task implement either a PPG-to-BP…
Blood pressure estimationNeural Architecture SearchQuantizationregressionPITN: Physics-Informed Temporal Networks for Cuffless Blood Pressure Estimation
Monitoring blood pressure with non-invasive sensors has gained popularity for providing comfortable user experiences, one of which is a significant function of smart wearables. Although providing a comfortable user exper…
Blood pressure estimationContrastive LearningTime SeriesEfficient Multi-View Fusion and Flexible Adaptation to View Missing in Cardiovascular System Signals
The progression of deep learning and the widespread adoption of sensors have facilitated automatic multi-view fusion (MVF) about the cardiovascular system (CVS) signals. However, prevalent MVF model architecture often am…
Atrial Fibrillation DetectionBlood pressure estimationSleep StagingTransfoRhythm: A Transformer Architecture Conductive to Blood Pressure Estimation via Solo PPG Signal Capturing
Recent statistics indicate that approximately 1.3 billion individuals worldwide suffer from hypertension, a leading cause of premature death globally. Blood Pressure (BP) serves as a critical health indicator for accurat…
Blood pressure estimationElectrocardiography (ECG)Photoplethysmography (PPG)