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Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes
The analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks,...
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Noise robust automatic heartbeat classification system using support vector machine and conditional spectral moment
Heartbeat classification is central to the detection of the arrhythmia. For the effective heartbeat classification, the noise-robust features are...
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Ensemble classifier fostered detection of arrhythmia using ECG data
Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and function of the human heart. This is broadly employed in heart...
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Quantitative analysis of the impact of respiratory state on the heartbeat-induced movements of the heart and its substructures
PurposeThis study seeks to examine the influence of the heartbeat on the position, volume, and shape of the heart and its substructures during...
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A novel atrial fibrillation automatic detection algorithm based on ensemble learning and multi-feature discrimination
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia disorder that necessitates long-time electrocardiogram (ECG) data for clinical diagnosis,...
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Automatic detection of arrhythmias from an ECG signal using an auto-encoder and SVM classifier
Millions of people around the world are affected by arrhythmias, which are abnormal activities of the functioning of the heart. Most arrhythmias are...
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Independent Detection of T-Waves in Single Lead ECG Signal Using Continuous Wavelet Transform
IntroductionIn the ECG signals, T-waves play a very important role in the detection of cardiac arrest. During myocardial ischemia, the first...
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Phase Gradient Divergence for the Quantitative Detection of Focal Activation Events During Cardiac Fibrillation
PurposeAtrial fibrillation is the most common arrhythmia. Spiral wave and focal activation (FA) are known to play an important mechanistic role in...
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Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review
Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2–11%. For the roughly 75% of OHCAs that are...
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Automated detection of arrhythmia from electrocardiogram signal based on new convolutional encoded features with bidirectional long short-term memory network classifier
Early detection of cardiac arrhythmia is needed to reduce mortality. Automatically detecting the cardiac arrhythmias is a very challenging task. In...
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Enhanced premature ventricular contraction pulse detection and classification using deep convolutional neural network
Access to accurate and precise monitoring systems for cardiac arrhythmia could contribute significantly to preventing damage and subsequent heart...
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Reduction of auditory input improves performance on the heartbeat tracking task, but does not necessarily enhance interoception
Previous research utilising a between-subjects design has indicated that the use of noise-dampening ear protectors might enhance interoceptive...
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An Effective Integrated Framework for Fetal QRS Complex Detection Based on Abdominal ECG Signal
PurposeNon-invasive fetal electrocardiography (fECG) has a promising application prospect in offering crucial information for assessing early...
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Detection of fetal arrhythmia by adaptive single channel electrocardiogram extraction
Fetal arrhythmia, the abnormal heartbeat of a fetus is broadly classified as tachy arrhythmia (too fast > 160 beats/min) and brady arrhythmia (too...
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Arrhythmia detection and classification using ECG and PPG techniques: a review
Electrocardiogram (ECG) and photoplethysmograph (PPG) are non-invasive techniques that provide electrical and hemodynamic information of the heart,...
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A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems....
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A Signal Processing Framework for the Detection of Abnormal Cardiac Episodes
MotivationCardiologists rely on the long duration Holter electrocardiogram (ECG) recordings in general for assessment of abnormal episodes and such...
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A systematic review of physiological signals based driver drowsiness detection systems
Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and...
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COVID-19’s influence on cardiac function: a machine learning perspective on ECG analysis
In December 2019, the spread of the SARS-CoV-2 virus to the world gave rise to probably the biggest public health problem in the world: the COVID-19...
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Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction
Although artificial intelligence (AI) algorithms have been shown to be capable of identifying cardiac dysfunction, defined as ejection fraction (EF)...
