Multi-Source Causal Invariance for Cuffless Blood Pressure Estimation Based on Photoplethysmography Signal Features
Cuffless continuous blood pressure (BP) monitoring is essential for personal health management. However, its accuracy is challenged by the diversity and heterogeneity of physiological data sources. We propose a multi-source feature selection framework based on Markov blanket theory and the concept o...
Saved in:
| Main Authors: | Yiliu Xu, Zhaoming He, Hao Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/11/3254 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Two-Branch ResNet-BiLSTM Deep Learning Framework for Extracting Multimodal Features Applied to PPG-Based Cuffless Blood Pressure Estimation
by: Zenan Liu, et al.
Published: (2025-06-01) -
Cuffless Blood Pressure Monitor for Home and Hospital Use
by: Toshiyo Tamura, et al.
Published: (2025-01-01) -
The quest for blood pressure markers in photoplethysmography and its applications in digital health
by: Josep Sola, et al.
Published: (2025-04-01) -
Conformal prediction quantifies wearable cuffless blood pressure with certainty
by: Zhan Shen, et al.
Published: (2025-07-01) -
UTransBPNet for cuffless and calibration-free blood pressure estimation under dynamic conditions
by: Yali Zheng, et al.
Published: (2025-05-01)