ReviewBioMed research international2022
Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals.
Review in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Personalized Calibration and Hybrid Feature Fusion for Continuous Blood Pressure Estimation Using PPG and ECG Signals.Sensors (Basel, Switzerland) · 2026Article
- Optical methods for cuffless blood pressure measurements.Biophotonics discovery · 2026Review
- The Challenge of Measuring Exercise: Advancing Metrological Barriers in Wearable Sensing.JMIR mHealth and uHealth · 2025Review
- Interventional study of the iSelfie heart health tool for assessment of vital signs (heart rate, blood pressure, and Oxygen Saturation) in the Kingdom of Saudi Arabia.Saudi medical journal · 2025Article
- Speckle contrast optical spectroscopy for cuffless blood pressure estimation based on microvascular blood flow and volume oscillations.Biomedical optics express · 2025Article
- Cuffless Blood Pressure Measurement: Where Do We Actually Stand?Hypertension (Dallas, Tex. : 1979) · 2025Review
- Machine Learning-Based VOBiosensors · 2025Article
- History and evolution of blood pressure measurement.Clinical hypertension · 2024Review
- PPG Signals-Based Blood-Pressure Estimation Using Grid Search in Hyperparameter Optimization of CNN-LSTM.Diagnostics (Basel, Switzerland) · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To review the progress of research on photoplethysmography- (PPG-) based cuffless continuous blood pressure monitoring technologies and prospect the challenges that need to be addressed in the future. Methods: Using Web of Science and PubMed as search engines, the literature on cuffless continuous blood pressure studies using PPG signals in the recent five years were searched. Results: Based on the retrieved literature, this paper describes the available open datasets, commonly used signal preprocessing methods, and model evaluation criteria. Early researches employed multisite PPG signals to calculate pulse wave velocity or time and predicted blood pressure by a simple linear equation. Later, extensive researches were dedicated to mine the features of PPG signals related to blood pressure and regressed blood pressure by machine learning models. Most recently, many researches have emerged to experiment with complex deep learning models for blood pressure prediction with the raw PPG signal as input. Conclusion: This paper summarized the methods in the retrieved literature, provided insight into the artificial intelligence algorithms employed in the literature, and concluded with a discussion of the challenges and opportunities for the development of cuffless continuous blood pressure monitoring technologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.