Cuffless Blood Pressure Estimation

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1 paper in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.

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ExpertoRhythm: Morphology-Aware Learning for Waveform Reconstruction and Cuffless Blood Pressure Estimation from Single-Channel PPG
Sep 28, 2026Amir Arjomand, Kenneth B. Kent, Georgiy KrylovPhotoplethysmography Wearable Health Monitoring
University of New Brunswick, Fredericton, Canada
SIFPBPNet: A Dual-Path Network for Wearable and Cuffless Blood Pressure Estimation via Individualized Steady-state Representation
Sep 11, 2026Shuailong Tang, Xiaoyu Li, Donglin Xie +4Photoplethysmography Wearable Health Monitoring
Shenzhen Technology University, Shenzhen, China · OPPO Health Lab, Shenzhen, China · Peking University, Beijing, China +1
Physics-Constrained Deep Learning Model for Contactless Blood Pressure Monitoring from Triaxial Bodyseismography
Aug 24, 2026Yuanyuan Zhang, Yida Zhang, Jiahui Li +6Physics-Informed ML Wearable Health Monitoring
School of Electrical and Computer Engineering, University of Georgia, Athens, 30603, United States · School of Computing, University of Georgia, Athens, 30603, United States · Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, 94305, United States +1
A Multidimensional Data-Driven Hybrid Transformer Framework for Non-invasive Continuous Blood Pressure Prediction
Aug 24, 2026Yuexin Ma, Jingqi Hou, Yuxuan Kang +1Wearable Health Monitoring Time Series Transformers
College of Computer Science, Beijing University of Technology, Beijing, China
Change Point--Aware Evaluation and Re-Calibration of PPG-Based Blood Pressure Estimation
Aug 19, 2026Yunwon Tae, Minje Park, Gyunho Rho +2Cuffless Blood Pressure Estimation Post-Hoc Calibration
VUNO Inc. · University of California, Irvine · Research Institute for Future Medicine, Samsung Medical Center +1
Personalized and Explainable Blood Pressure Estimation from PPG via Hybrid CNN--Morphological Features
Aug 11, 2026Myung-Kyu Yi, Jongshill Lee, Jeyeon Lee +1Cuffless Blood Pressure Estimation Photoplethysmography
Department of Biomedical Engineering, Hanyang University,, Seoul 04763, South Korea
Single-Beat Cuffless Blood Pressure Estimation Using Ear-PPG and ECG with a Lightweight Hybrid Learning Framework
Jul 29, 2026Kindeep K. Dhatt, Tengyue Wu, Hanbang Hua +1Wearable Health Monitoring Cuffless Blood Pressure Estimation
1. Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville, TN, 37232 · 6. Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235 · 2. Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, 37235 +3
Blood Pressure Estimation from PPG: A Comparative Study of Direct and ECG-Mediated Deep Learning Pipelines
Jul 26, 2026Bo Wu, Haoling Wang, Zhuodiao Kuang +1Photoplethysmography Wearable Health Monitoring
Department of Informatics and Networked Systems University of Pittsburgh Pittsburgh, USA · Department of Biostatistics and Health Data Science University of Pittsburgh Pittsburgh, USA · Language Technologies Institute Carnegie Mellon University Pittsburgh, USA
DMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals
Jun 9, 2026Yidan Shen, Neville Mathew, Maham Rahimi +4Photoplethysmography Wearable Health Monitoring
Dept. of Electrical and Computer Engineering University of Houston Houston, USA · Dept. of Engineering Technology University of Houston Houston, USA · Dept. of Cardiovascular Surgery Houston Methodist Hospital Houston, USA +1
Uncertainty Reliability Under Domain Shift: An Investigation for Data-Driven Blood Pressure Estimation in Photoplethysmography
May 18, 2026Mohammad Moulaeifard, Ciaran Bench, Philip J. Aston +1Distribution Shift Robustness Post-Hoc Calibration
AI4Health Department, University of Oldenburg, Oldenburg, Germany · Department of Data Science and AI, National Physical Laboratory, Teddington, United Kingdom · School of Mathematics and Physics, University of Surrey, Surrey, United Kingdom
Attractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography
May 11, 2026Timothy Oladunni, Farouk Ganiyu AdewumiDynamical Systems Photoplethysmography
Department of Computer Science, Morgan State University, Baltimore, MD 21251 USA
A Hybrid Windkessel-Neural Approach for Improved Noninvasive Blood Pressure Monitoring
Apr 21, 2026Vaibhav Gollapalli, Aniruth AnanthanarayananPhysics-Informed ML Wearable Health Monitoring
Department of Physics University of North Texas Denton, United States of America
End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables
Apr 11, 2026Francesco Carlucci, Giovanni Pollo, Xiaying Wang +6Cuffless Blood Pressure Estimation Wearable Health Monitoring
Interuniversity Department of Regional and Urban Studies and Planning at Politecnico di Torino, Torino, Italy · Department of Control and Computer Engineering at Politecnico di Torino, Torino, Italy · Department of Information Technology and Electrical Engineering at ETH Zurich, Zurich, Switzerland +1
Deriving Health Metrics from the Photoplethysmogram: Benchmarks and Insights from MIMIC-III-Ext-PPG
Mar 23, 2026Mohammad Moulaeifard, Philip J. Aston, Peter H. Charlton +1Clinical Prediction Photoplethysmography
AI4Health Department, Oldenburg University, Oldenburg, Germany · Department of Data Science and AI, National Physical Laboratory, Teddington, United Kingdom · School of Mathematics and Physics, University of Surrey, Guildford, United Kingdom +1

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ExpertoRhythm: Morphology-Aware Learning for Waveform Reconstruction and Cuffless Blood Pressure Estimation from Single-Channel PPG

Amir Arjomand, Kenneth B. Kent, Georgiy Krylov

University of New Brunswick, Fredericton, Canada

Photoplethysmography Wearable Health Monitoring Cuffless Blood Pressure Estimation

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Continuous cuffless blood pressure (BP) monitoring from photoplethysmography (PPG) has strong potential for wearable health and telemonitoring, but accurate estimation remains difficult because PPG-to-BP mapping must preserve subtle waveform morphology and pressure-range-dependent dynamics. We introduce ExpertoRhythm, an attention-enhanced 1D U-Net that reconstructs the arterial blood pressure (ABP) waveform from a single-channel PPG signal and derives systolic and diastolic BP directly from the reconstructed waveform. The central contribution is a composite morphology-aware learning objective that integrates range-weighted SmoothL1 reconstruction with a window-range regularizer to emphasize high-dynamic BP segments and reduce amplitude under/over-shoot. On the UCI cuff-less BP dataset with 942 subjects, ExpertoRhythm achieves 2.46/1.46 mmHg MAE for systolic/diastolic BP (SBP/DBP), while obtaining a 30.4% average relative error reduction over pure MSE across waveform reconstruction and BP estimation metrics. Clinical-style evaluation further demonstrates low bias and strong agreement across the BP range, including high-pressure windows up to 200 mmHg, satisfying AAMI criteria and achieving BHS Grade A. These results suggest that morphology-aware waveform reconstruction from a single PPG channel can provide an accurate and practical pathway toward continuous cuffless BP monitoring in wearable and remote-care settings.