AIMC Topic: Blood Pressure

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Novel parameters for predicting fluid responsiveness during the mini fluid challenge and ability of the cardiac power index: an observational cohort study.

Turkish journal of medical sciences
BACKGROUND/AIM: The percentage change in the stroke volume index (SVI) due to the mini fluid challenge (MFC) (MFC-ΔSVI%) is used commonly in daily practice. However, up to 20% of patients remain in the gray zone of this variable. Thus, it was aimed t...

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array.

Science advances
Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide a...

Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.

BMC medical informatics and decision making
BACKGROUND: Monitoring 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 measureme...

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
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)
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...

Predicting dry weight change in Hemodialysis patients using machine learning.

BMC nephrology
BACKGROUND: Machine Learning has been increasingly used in the medical field, including managing patients undergoing hemodialysis. The random forest classifier is a Machine Learning method that can generate high accuracy and interpretability in the d...

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives.

Sensors (Basel, Switzerland)
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 ...

Hemodynamic study of blood flow in the aorta during the interventional robot treatment using fluid-structure interaction.

Biomechanics and modeling in mechanobiology
An interventional robot is a means for vascular diagnosis and treatment, and it can perform dredging, releasing drug and operating. Normal hemodynamic indicators are a prerequisite for the application of interventional robots. The current hemodynamic...

Deep Learning-Based Non-Contact IPPG Signal Blood Pressure Measurement Research.

Sensors (Basel, Switzerland)
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
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...