AIMC Topic: Arrhythmias, Cardiac

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Using a Calculated Pulse Rate with an Artificial Neural Network to Detect Irregular Interbeats.

Journal of medical systems
Heart rate is an important clinical measure that is often used in pathological diagnosis and prognosis. Valid detection of irregular heartbeats is crucial in the clinical practice. We propose an artificial neural network using the calculated pulse ra...

An Automatic Subject-Adaptable Heartbeat Classifier Based on Multiview Learning.

IEEE journal of biomedical and health informatics
In this paper, a novel subject-adaptable heartbeat classification model is presented, in order to address the significant interperson variations in ECG signals. A multiview learning approach is proposed to automate subject adaptation using a small am...

Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine.

Computers in biology and medicine
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Automatic detection of AF could substantially help in early diagnosis, management and co...

Stabilization of the human heartbeat using adaptive controller-based optimized deep policy gradient.

Computers in biology and medicine
Stabilizing the cardiac rhythm is imperative for preserving cardiovascular health and preventing life-threatening arrhythmias. The stabilization of the heartbeat through traditional control methods presents significant challenges due to the intricate...

A hybrid approach for machine learning based beat classification of ECG using different digital differentiators and DTCWT.

Computers in biology and medicine
This research paper presents a systematic approach to ECG beat classification using advanced machine learning techniques. The study classifies ECG beats into six distinct classes based on annotations from the MIT-BIH Arrhythmia Database. The methodol...

A hybrid machine learning approach using particle swarm optimization for cardiac arrhythmia classification.

International journal of cardiology
BACKGROUND: Precise and rapid identification of cardiac arrhythmias is paramount for delivering optimal patient care. Machine learning (ML) techniques hold significant promise for classifying arrhythmias, yet achieving peak performance often necessit...

Traditional Chinese Medicine for Anti-Arrhythmias: Mechanisms via Potassium Channels.

Basic & clinical pharmacology & toxicology
Cardiac arrhythmia is a common life-threatening cardiovascular disorder. Potassium channels play a crucial role in cardiac electrophysiology, and their dysfunction is closely associated with the occurrence and development of arrhythmia. Traditional C...

A multi-scale convolutional LSTM-dense network for robust cardiac arrhythmia classification from ECG signals.

Computers in biology and medicine
Cardiac arrhythmias are irregular heart rhythms that, if undetected, can lead to severe cardiovascular conditions. Detecting these anomalies early through electrocardiogram (ECG) signal analysis is critical for preventive healthcare and effective tre...

Telecardiology unleashed: probing the depths of effectiveness in remote monitoring and telemedicine applications for acute cardiac conditions.

European heart journal. Acute cardiovascular care
Telecardiology has emerged as a promising approach in acute cardiac care through advancements in digital health technologies. This review explores the current evidence of telemedicine applications in acute coronary syndrome, arrhythmias, and acute he...