ArticleBMC medical informatics and decision making2023
Non-invasive arterial blood pressure measurement and SpO
Article in BMC medical informatics and decision making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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.
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Who cites it
22 citing papers in PubMed, 50 citations in OpenAlex.
- A wearable cuffless blood pressure monitoring system: real-time measurement using force sensing and waveform analysis.Journal of clinical monitoring and computing · 2026Article
- A multitask Transformer-VAE framework for robust PPG denoising and atrial fibrillation screening.BMC medical imaging · 2026Article
- Reliable wrist PPG monitoring by mitigating poor skin sensor contact.Scientific reports · 2025Article
- 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
- A 1-Dimensional Physiological Signal Prediction Method Based on Composite Feature Preprocessing and Multi-Scale Modeling.Sensors (Basel, Switzerland) · 2025Article
- PPG-Net 4: Deep-Learning-Based Approach for Classification of Blood Flow Using Non-Invasive Dual Photoplethysmography (PPG) Signals.Sensors (Basel, Switzerland) · 2025Article
- Machine Learning Prediction of Mean Arterial Pressure from the Photoplethysmography Waveform During Hemorrhagic Shock and Fluid Resuscitation.Sensors (Basel, Switzerland) · 2025Article
- Skin-Inspired Healthcare Electronics.Biomimetics (Basel, Switzerland) · 2025Review
- Noninvasive On-Skin Biosensors for Monitoring Diabetes Mellitus.Nano-micro letters · 2025Review
- Assessment of photoplethysmography-based blood pressure determinations during long-term and short-term remote cardiac monitoring: the RECAMO study.European heart journal. Digital health · 2025Article
- A comprehensive review of heart rate measurement using remote photoplethysmography and deep learning.Biomedical engineering online · 2025Review
- Design and validation of a novel multiple sites signal acquisition and analysis system based on pressure stimulation for human cardiovascular information.Scientific reports · 2025Article
- Article
- Evaluating AI Methods for Pulse Oximetry: Performance, Clinical Accuracy, and Comprehensive Bias Analysis.Bioengineering (Basel, Switzerland) · 2024Article
- Accurate and 30-plus days reliable cuffless blood pressure measurements with 9-minutes personal photoplethysmograph data and mixed deduction learning.Scientific reports · 2024Article
- Transforming Healthcare: The AI Revolution in the Comprehensive Care of Hypertension.Clinics and practice · 2024Review
- Preserving shape details of pulse signals for video-based blood pressure estimation.Biomedical optics express · 2024Article
- ACNN-BiLSTM: A Deep Learning Approach for Continuous Noninvasive Blood Pressure Measurement Using Multi-Wavelength PPG Fusion.Bioengineering (Basel, Switzerland) · 2024Article
- Towards Non-Invasive and Continuous Blood Pressure Monitoring in Neonatal Intensive Care Using Artificial Intelligence: A Narrative Review.Healthcare (Basel, Switzerland) · 2023Review
- Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMonitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measurement methods have intrinsic limitations; for instance, arterial blood pressure is measured by inserting a catheter in the artery causing discomfort and infection.
methodPhotoplethysmogram (PPG) signals can be collected via non-invasive devices, and therefore have stimulated researchers' interest in exploring blood pressure estimation using machine learning and PPG signals as a non-invasive alternative. In this paper, we propose a Transformer-based deep learning architecture that utilizes PPG signals to conduct a personalized estimation of arterial systolic blood pressure, arterial diastolic blood pressure, and oxygen saturation.
resultsThe proposed method was evaluated with a subset of 1,732 subjects from the publicly available ICU dataset MIMIC III. The mean absolute error is 2.52 ± 2.43 mmHg for systolic blood pressure, 1.37 ± 1.89 mmHg for diastolic blood pressure, and 0.58 ± 0.79% for oxygen saturation, which satisfies the requirements of the Association of Advancement of Medical Instrumentation standard and achieve grades A for the British Hypertension Society standard.
conclusionsThe results indicate that our model meets clinical standards and could potentially boost the accuracy of blood pressure and oxygen saturation measurement to deliver high-quality healthcare.
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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.