AIMC Topic: Heart Rate

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Deep Learning-Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms.

Computational intelligence and neuroscience Aug 11, 2022
Automated ECG-based arrhythmia detection is critical for early cardiac disease prevention and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia detection with great success. However, the lack of labeled ECG data an...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Deep Learning Algorithms Heart Rate Electrocardiography
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Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique.

Sensors (Basel, Switzerland) Jul 27, 2022
Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost importance to be able to efficiently diagnose these arrhythmias promptly. There exist many techniques for the detection of arrhythmias; however, the most widely a...
Arrhythmias, Cardiac Heart Rate Algorithms Deep Learning Electrocardiography Signal Processing, Computer-Assisted Humans
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A deep learning approach to estimate pulse rate by remote photoplethysmography.

Physiological measurement Jul 25, 2022
This study proposes a U-net shaped Deep Neural Network (DNN) model to extract remote photoplethysmography (rPPG) signals from skin color signals to estimate Pulse Rate (PR).Three input window sizes are used in the DNN: 256 samples (5.12 s), 512 sampl...
Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Heart Rate Deep Learning Photoplethysmography
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Photoplethysmogram based vascular aging assessment using the deep convolutional neural network.

Scientific reports Jul 5, 2022
Arterial stiffness due to vascular aging is a major indicator during the assessment of cardiovascular risk. In this study, we propose a method for age estimation by applying deep learning to a photoplethysmogram (PPG) for the non-invasive assessment ...
Neural Networks, Computer Artificial Intelligence Photoplethysmography Heart Rate
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A Modified Deep Learning Framework for Arrhythmia Disease Analysis in Medical Imaging Using Electrocardiogram Signal.

BioMed research international Jul 4, 2022
Arrhythmias are anomalies in the heartbeat rhythm that occur occasionally in people's lives. These arrhythmias can lead to potentially deadly consequences, putting your life in jeopardy. As a result, arrhythmia identification and classification are a...
Databases, Factual Heart Rate Deep Learning Neural Networks, Computer Humans Algorithms Electrocardiography Signal Processing, Computer-Assisted Diagnostic Imaging Arrhythmias, Cardiac
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Frailty Identification Using Heart Rate Dynamics: A Deep Learning Approach.

IEEE journal of biomedical and health informatics Jul 1, 2022
Previous research showed that frailty can influence autonomic nervous system and consequently heart rate response to physical activities, which can ultimately influence the homeostatic state among older adults. While most studies have focused on rest...
Heart Rate Frail Elderly Geriatric Assessment Humans Aged Deep Learning Frailty
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XGBoost Regression of the Most Significant Photoplethysmogram Features for Assessing Vascular Aging.

IEEE journal of biomedical and health informatics Jul 1, 2022
The purpose of this study was to confirm the potential of XGBoost as a vascular aging assessment model based on the photoplethysmogram (PPG) features suggested in previous studies, and to explore the key PPG features for vascular aging assessment thr...
Humans Photoplethysmography Artificial Intelligence Heart Rate Aging
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Electrocardiogram analysis of post-stroke elderly people using one-dimensional convolutional neural network model with gradient-weighted class activation mapping.

Artificial intelligence in medicine Jun 30, 2022
Stroke is the second leading cause of death globally after ischemic heart disease, also a risk factor of cardioembolic stroke. Thus, we postulate that heartbeats encapsulate vital signals related to stroke. With the rapid advancement of deep neural n...
Heart Rate ROC Curve Electrocardiography Humans Neural Networks, Computer Aged
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Cost-Sensitive Learning for Anomaly Detection in Imbalanced ECG Data Using Convolutional Neural Networks.

Sensors (Basel, Switzerland) May 27, 2022
Arrhythmia detection algorithms based on deep learning are attracting considerable interest due to their vital role in the diagnosis of cardiac abnormalities. Despite this interest, deep feature representation for ECG is still challenging and intrigu...
Electrocardiography Arrhythmias, Cardiac Heart Rate Neural Networks, Computer Humans Algorithms
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A Neuromorphic Model With Delay-Based Reservoir for Continuous Ventricular Heartbeat Detection.

IEEE transactions on bio-medical engineering May 19, 2022
There is a growing interest in neuromorphic hardware since it offers a more intuitive way to achieve bio-inspired algorithms. This paper presents a neuromorphic model for intelligently processing continuous electrocardiogram (ECG) signal. This model ...
Humans Heart Rate Electrocardiography Signal Processing, Computer-Assisted Neural Networks, Computer Algorithms
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