AIMC Topic: Heart Rate
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Combined deep CNN-LSTM network-based multitasking learning architecture for noninvasive continuous blood pressure estimation using difference in ECG-PPG features.
Scientific reports
Jun 29, 2021
The pulse arrival time (PAT), the difference between the R-peak time of electrocardiogram (ECG) signal and the systolic peak of photoplethysmography (PPG) signal, is an indicator that enables noninvasive and continuous blood pressure estimation. Howe...
Portable Interactive Pulse Tactile Recorder and Player System.
Sensors (Basel, Switzerland)
Jun 25, 2021
Pulse palpation is an effective method for diagnosing arterial diseases. However, most pulse measurement devices use preconfigured pressures to collect pulse signals, and most pulse tactile simulators can only display standard or predefined pulse wav...
Deep learning-based photoplethysmography classification for peripheral arterial disease detection: a proof-of-concept study.
Physiological measurement
Jun 17, 2021
A proof-of-concept study to assess the potential of a deep learning (DL) based photoplethysmography PPG ('DLPPG') classification method to detect peripheral arterial disease (PAD) using toe PPG signals.PPG spectrogram images derived from our previous...
Biomarker-Informed Machine Learning Model of Cognitive Fatigue from a Heart Rate Response Perspective.
Sensors (Basel, Switzerland)
Jun 2, 2021
Cognitive fatigue is a psychological state characterised by feelings of tiredness and impaired cognitive functioning arising from high cognitive demands. This paper examines the recent research progress on the assessment of cognitive fatigue and prov...
Blood Biomarkers Predict Cardiac Workload Using Machine Learning.
BioMed research international
Jun 1, 2021
INTRODUCTION: Rate pressure product (the product of heart rate and systolic blood pressure) is a measure of cardiac workload. Resting rate pressure product (rRPP) varies from one individual to the next, but its biochemical/cellular phenotype remains ...
A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods.
Sensors (Basel, Switzerland)
May 27, 2021
The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning metho...
Machine learning prediction of sleep stages in dairy cows from heart rate and muscle activity measures.
Scientific reports
May 25, 2021
Sleep is important for cow health and shows promise as a tool for assessing welfare, but methods to accurately distinguish between important sleep stages are difficult and impractical to use with cattle in typical farm environments. The objective of ...
Impact of ECG Characteristics on the Performance of an Artificial Intelligence Enabled ECG for Predicting Left Ventricular Dysfunction.
Circulation. Arrhythmia and electrophysiology
May 17, 2021
ECG Heartbeat Classification Based on an Improved ResNet-18 Model.
Computational and mathematical methods in medicine
Apr 30, 2021
Based on a convolutional neural network (CNN) approach, this article proposes an improved ResNet-18 model for heartbeat classification of electrocardiogram (ECG) signals through appropriate model training and parameter adjustment. Due to the unique r...
Interpretable heartbeat classification using local model-agnostic explanations on ECGs.
Computers in biology and medicine
Apr 16, 2021
Treatment and prevention of cardiovascular diseases often rely on Electrocardiogram (ECG) interpretation. Dependent on the physician's variability, ECG interpretation is subjective and prone to errors. Machine learning models are often developed and ...
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