Intrinsic PPG–ECG Coupling for Accurate and Low‐Power Blood Pressure Monitoring

Long-term, continuous blood pressure (BP) monitoring is of great clinical importance for the early diagnosis and dynamic assessment of cardiovascular diseases. Conventional BP monitoring methods based on pulse transit time (PTT) typically rely on at least two independent signal channels. However, multi-signal processing introduces synchronization errors and inaccuracies in fiducial point detection, thereby limiting the accuracy and efficiency of BP estimation. In addition, recording and processing multiple signals increases circuit complexity and elevates system power consumption. To overcome these limitations, we propose an intrinsic signal synchronization strategy based on photoplethysmography-electrocardiogram (PPG-ECG) signal coupling. By fusing PPG and ECG signals into a unified waveform that preserves the essential features of both, intrinsic synchronization is inherently achieved. Compared with conventional independent signal processing, this approach reduces PTT error to less than 15 ms and achieves a PTT detection rate exceeding 98%. Furthermore, the data load is significantly reduced, resulting in a 43.75% decrease in system power consumption. Based on this principle, we developed a compact, lightweight, chest wearable sensor patch. The device demonstrates high BP measurement accuracy (ME ≤ 5 mmHg, STD ≤ 8 mmHg) across diverse scenarios, including both static and dynamic BP conditions. This strategy not only simplifies the design and manufacturing of BP monitoring devices but also enhances their performance in terms of accuracy, energy efficiency, and operational lifetime.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-03-03
DOI
https://doi.org/10.1002/advs.202520101
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intrinsic PPG–ECG Coupling for Accurate and Low‐Power Blood Pressure Monitoring

Hua Luo, Xiaodong Wu, Zhentao Yao, Sitong Chen et al.
Advanced Science
Non-Invasive Vital Sign Monitoring
article

Intrinsic PPG–ECG Coupling for Accurate and Low‐Power Blood Pressure Monitoring

Hua Luo, Xiaodong Wu, Zhentao Yao, Sitong Chen, Zhou Jiang, Hanmin Liu
article en

Abstract

Long-term, continuous blood pressure (BP) monitoring is of great clinical importance for the early diagnosis and dynamic assessment of cardiovascular diseases. Conventional BP monitoring methods based on pulse transit time (PTT) typically rely on at least two independent signal channels. However, multi-signal processing introduces synchronization errors and inaccuracies in fiducial point detection, thereby limiting the accuracy and efficiency of BP estimation. In addition, recording and processing multiple signals increases circuit complexity and elevates system power consumption. To overcome these limitations, we propose an intrinsic signal synchronization strategy based on photoplethysmography-electrocardiogram (PPG-ECG) signal coupling. By fusing PPG and ECG signals into a unified waveform that preserves the essential features of both, intrinsic synchronization is inherently achieved. Compared with conventional independent signal processing, this approach reduces PTT error to less than 15 ms and achieves a PTT detection rate exceeding 98%. Furthermore, the data load is significantly reduced, resulting in a 43.75% decrease in system power consumption. Based on this principle, we developed a compact, lightweight, chest wearable sensor patch. The device demonstrates high BP measurement accuracy (ME ≤ 5 mmHg, STD ≤ 8 mmHg) across diverse scenarios, including both static and dynamic BP conditions. This strategy not only simplifies the design and manufacturing of BP monitoring devices but also enhances their performance in terms of accuracy, energy efficiency, and operational lifetime.

Advanced Science
Sichuan University (CN), West China Second University Hospital of Sichuan University (CN), Maternal and Child Health Hospital of Sichuan Province (CN), Chengdu University (CN)
Affordable and clean energy
Openalex Percentile: Top 38%
Non-Invasive Vital Sign Monitoring
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.