AIMC Topic: Photoplethysmography
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Non-Invasive Estimation of Hemoglobin Using a Multi-Model Stacking Regressor.
IEEE journal of biomedical and health informatics
Nov 20, 2019
OBJECTIVE: We describe a novel machine-learning based method to estimate total Hemoglobin (Hb) using photoplethysmograms (PPGs) acquired non-invasively.
Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.
Computers in biology and medicine
Oct 17, 2019
UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA impairment is an active field of research interest. A breath-hold challenge is usually used in clinical and research settings to simulate cardiovascul...
SVR ensemble-based continuous blood pressure prediction using multi-channel photoplethysmogram.
Computers in biology and medicine
Aug 19, 2019
In this paper, a continuous non-occluding blood pressure (BP) prediction method is proposed using multiple photoplethysmogram (PPG) signals. In the new method, BP is predicted by a committee machine or ensemble learning framework comprising multiple ...
Machine Learning Classification for Assessing the Degree of Stenosis and Blood Flow Volume at Arteriovenous Fistulas of Hemodialysis Patients Using a New Photoplethysmography Sensor Device.
Sensors (Basel, Switzerland)
Aug 4, 2019
The classifier of support vector machine (SVM) learning for assessing the quality of arteriovenous fistulae (AVFs) in hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor device is presented in this work. In clinical practice, the...
Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks.
Sensors (Basel, Switzerland)
Jul 12, 2019
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a number of domains, e.g., for healthcare or fitness applications. Recently, methods based on time-frequency spectra emerged to address the challenges of motion artefac...
Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study.
JMIR mHealth and uHealth
Jun 6, 2019
BACKGROUND: Wearable devices have evolved as screening tools for atrial fibrillation (AF). A photoplethysmographic (PPG) AF detection algorithm was developed and applied to a convenient smartphone-based device with good accuracy. However, patients wi...
A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning.
Sensors (Basel, Switzerland)
Jun 6, 2019
Considering the existing issues of traditional blood pressure (BP) measurement methods and non-invasive continuous BP measurement techniques, this study aims to establish the systolic BP and diastolic BP estimation models based on machine learning us...
A Supervised Approach to Robust Photoplethysmography Quality Assessment.
IEEE journal of biomedical and health informatics
Apr 3, 2019
Early detection of Atrial Fibrillation (AFib) is crucial to prevent stroke recurrence. New tools for monitoring cardiac rhythm are important for risk stratification and stroke prevention. As many of new approaches to long-term AFib detection are now ...
A Deep Neural Network-Based Pain Classifier Using a Photoplethysmography Signal.
Sensors (Basel, Switzerland)
Jan 18, 2019
Side effects occur when excessive or low doses of analgesics are administered compared to the required amount to mediate the pain induced during surgery. It is important to accurately assess the pain level of the patient during surgery. We proposed a...
CorNET: Deep Learning Framework for PPG-Based Heart Rate Estimation and Biometric Identification in Ambulant Environment.
IEEE transactions on biomedical circuits and systems
Jan 10, 2019
Advancements in wireless sensor network technologies have enabled the proliferation of miniaturized body-worn sensors, capable of long-term pervasive biomedical signal monitoring. Remote cardiovascular monitoring has been one of the beneficiaries of ...
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