AIMC Topic: Blood Pressure Determination
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Personalized Machine Learning-Coupled Nanopillar Triboelectric Pulse Sensor for Cuffless Blood Pressure Continuous Monitoring.
ACS nano
Nov 20, 2023
A wearable system that can continuously track the fluctuation of blood pressure (BP) based on pulse signals is highly desirable for the treatments of cardiovascular diseases, yet the sensitivity, reliability, and accuracy remain challenging. Since th...
Blood pressure estimation and classification using a reference signal-less photoplethysmography signal: a deep learning framework.
Physical and engineering sciences in medicine
Sep 25, 2023
The markers that help to predict th function of a cardiovascular system are hemodynamic parameters like blood pressure (BP), stroke volume, heart rate, and cardiac output. Continuous analysis of hemodynamic parameters such as BP can detect abnormalit...
A novel CS-NET architecture based on the unification of CNN, SVM and super-resolution spectrogram to monitor and classify blood pressure using photoplethysmography.
Computer methods and programs in biomedicine
Jul 16, 2023
CONTEXT: Continuous blood pressure (BP) monitoring plays an important role while treating various cardiovascular diseases and hypertension. A high correlation between arterial blood pressure (ABP) and Photoplethysmogram (PPG) signal enables using a P...
Continuous Blood Pressure Monitoring in Patients Having Surgery: A Narrative Review.
Medicina (Kaunas, Lithuania)
Jul 14, 2023
Hypotension can occur before, during, and after surgery and is associated with postoperative complications. Anesthesiologists should thus avoid profound and prolonged hypotension. A crucial part of avoiding hypotension is accurate and tight blood pre...
Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives.
Sensors (Basel, Switzerland)
Jun 20, 2023
The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive ...
Deep Learning-Based Non-Contact IPPG Signal Blood Pressure Measurement Research.
Sensors (Basel, Switzerland)
Jun 13, 2023
In this paper, a multi-stage deep learning blood pressure prediction model based on imaging photoplethysmography (IPPG) signals is proposed to achieve accurate and convenient monitoring of human blood pressure. A camera-based non-contact human IPPG s...
Deep-learning-based blood pressure estimation using multi channel photoplethysmogram and finger pressure with attention mechanism.
Scientific reports
Jun 8, 2023
Recently, several studies have proposed methods for measuring cuffless blood pressure (BP) using finger photoplethysmogram (PPG) signals. This study presents a new BP estimation system that measures PPG signals under progressive finger pressure, maki...
A deep learning method for continuous noninvasive blood pressure monitoring using photoplethysmography.
Physiological measurement
May 22, 2023
. The aim of this study is to investigate continuous blood pressure waveform estimation from a plethysmography (PPG) signal, thus providing more human cardiovascular status information than traditional cuff-based methods.. The proposed method utilize...
Data-Driven Guided Attention for Analysis of Physiological Waveforms With Deep Learning.
IEEE journal of biomedical and health informatics
Nov 10, 2022
Estimating physiological parameters - such as blood pressure (BP) - from raw sensor data captured by noninvasive, wearable devices rely on either burdensome manual feature extraction designed by domain experts to identify key waveform characteristics...
Advances in Cuffless Continuous Blood Pressure Monitoring Technology Based on PPG Signals.
BioMed research international
Oct 1, 2022
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.
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