A paralleled CNN and Transformer network for PPG-based cuff-less blood pressure estimation
Authors:
- Zhonghe TianZTZhonghe Tian
- Aiping LiuALAiping Liu
- Guokang ZhuGZGuokang Zhu
- Xun ChenXCXun Chen
- 16 September 2024
- journal article
- research article
- Published by Elsevier in Biomedical Signal Processing and Control
- Vol. 99
Abstract
No abstract availableKeywords
This publication has 38 references indexed in Scilit:
- Continual learning for cuffless blood pressure estimationBiomedical Signal Processing and Control, 2024
- Hybrid modeling on reconstitution of continuous arterial blood pressure using finger photoplethysmographyBiomedical Signal Processing and Control, 2023
- Machine Learning for Hypertension Prediction: a Systematic ReviewCurrent Hypertension Reports, 2022
- Cuffless blood pressure estimation from PPG signals and its derivatives using deep learning modelsBiomedical Signal Processing and Control, 2021
- Deep generative model with domain adversarial training for predicting arterial blood pressure waveform from photoplethysmogram signalBiomedical Signal Processing and Control, 2021
- Deep learning models for cuffless blood pressure monitoring from PPG signals using attention mechanismBiomedical Signal Processing and Control, 2021
- Investigation on the effect of Womersley number, ECG and PPG features for cuff less blood pressure estimation using machine learningBiomedical Signal Processing and Control, 2020
- Cuffless blood pressure estimation from electrocardiogram and photoplethysmogram using waveform based ANN-LSTM networkBiomedical Signal Processing and Control, 2019
- Blood pressure estimation from appropriate and inappropriate PPG signals using A whole-based methodBiomedical Signal Processing and Control, 2019
- Derivation of respiration rate from ambulatory ECG and PPG using Ensemble Empirical Mode Decomposition: Comparison and fusionComputers in Biology and Medicine, 2017