ArticleJournal of clinical medicine2019
Analysis of Pulse Arrival Time as an Indicator of Blood Pressure in a Large Surgical Biosignal Database: Recommendations for Developing Ubiquitous Blood Pressure Monitoring Methods.
Article in Journal of clinical medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- The role of dataset integrity, calibration and signal quality in neural network-based blood pressure estimation.Scientific reports · 2026Article
- Innovative Wearable Platform for Synchronized Biosignals Acquisition: A Proof of Concept in a Cuff-Less Blood Pressure Monitoring Case Study.IEEE journal of translational engineering in health and medicine · 2026Article
- An Ensemble-Based AI Approach for Continuous Blood Pressure Estimation in Health Monitoring Applications.Sensors (Basel, Switzerland) · 2025Article
- Exploring the Effect of LED-to-Photodetector Spacing on Subcutaneous Photoplethysmography for Continuous Blood Pressure Measurement.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Machine learning based, subject-specific, gender and race independent, non-invasive estimation of the arterial blood pressure.NPJ cardiovascular health · 2025Article
- A method for blood pressure hydrostatic pressure correction using wearable inertial sensors and deep learning.Npj biosensing · 2025Article
- Non-invasive pulse arrival time is associated with cardiac index in pediatric heart transplant patients with normal ejection fraction.Physiological measurement · 2024Article
- Quantifying the Suitability of Biosignals Acquired During Surgery for Multimodal Analysis.IEEE open journal of engineering in medicine and biology · 2024Article
- Quantitative analysis of pulse arrival time and PPG morphological features based cuffless blood pressure estimation: a comparative study between diabetic and non-diabetic groups.Biomedical engineering letters · 2023Article
- Blood Pressure Measurement Based on the Camera and Inertial Measurement Unit of a Smartphone: Instrument Validation Study.JMIR mHealth and uHealth · 2023Article
- Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-Invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients.Sensors (Basel, Switzerland) · 2023Article
- Comparing Remote Speckle Plethysmography and Finger-Clip Photoplethysmography with Non-Invasive Finger Arterial Pressure Pulse Waves, Regarding Morphology and Arrival Time.Bioengineering (Basel, Switzerland) · 2023Article
- Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges.Bioengineering (Basel, Switzerland) · 2022Review
- Cuffless Blood Pressure Monitoring: Academic Insights and Perspectives Analysis.Micromachines · 2022Review
- Blood Pressure Response and Pulse Arrival Time During Exercise Testing in Well-Trained Individuals.Frontiers in physiology · 2022Article
- PulseDB: A large, cleaned dataset based on MIMIC-III and VitalDB for benchmarking cuff-less blood pressure estimation methods.Frontiers in digital health · 2022Article
- Prognosis of Diabetic Peripheral Neuropathy via Decomposed Digital Volume Pulse from the Fingertip.Entropy (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
As non-invasive continuous blood pressure monitoring (NCBPM) has gained wide attraction in the recent decades, many pulse arrival time (PAT) or pulse transit time (PTT) based blood pressure (BP) estimation studies have been conducted. However, most of the studies have used small homogeneous subject pools to generate models of BP based on particular interventions for induced hemodynamic change. In this study, a large open biosignal database from a diverse group of 2309 surgical patients was analyzed to assess the efficacy of PAT, PTT, and confounding factors on the estimation of BP. After pre-processing the dataset, a total of 6,777,308 data pairs of BP and temporal features between electrocardiogram (ECG) and photoplethysmogram (PPG) were extracted and analyzed. Correlation analysis revealed that PAT or PTT extracted from the intersecting-tangent (IT) point of PPG showed the highest mean correlation to BP. The mean correlation between PAT and systolic blood pressure (SBP) was -0.37 and the mean correlation between PAT and diastolic blood pressure (DBP) was -0.30, outperforming the correlation between BP and PTT at -0.12 for SBP and -0.11 for DBP. A linear model of BP with a simple calibration method using PAT as a predictor was developed which satisfied international standards for automatic oscillometric BP monitors in the case of DBP, however, SBP could not be predicted to a satisfactory level due to higher errors. Furthermore, multivariate regression analyses showed that many confounding factors considered in previous studies had inconsistent effects on the degree of correlation between PAT and BP.
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