Related Experiment Video

Updated: Apr 16, 2026

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

14.2K

Identifying Hypertrophic Cardiomyopathy Patients by Classifying Individual Heartbeats from 12-lead ECG Signals

Quazi Abidur Rahman1, Larisa G Tereshchenko2, Matthew Kongkatong3

  • 1Computational Biology and Machine Learning Lab, School of Computing, Queen's University, Kingston, ON, Canada.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine
|March 5, 2015
PubMed

Insights

Electrocardiogram (ECG) tests can detect hypertrophic cardiomyopathy (HCM). Our classifier identifies HCM using ECG signals, achieving high accuracy in distinguishing HCM patients from controls.

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Machine Learning

Background:

  • Hypertrophic cardiomyopathy (HCM) is a condition where heart muscle thickening obstructs blood flow.
  • Early detection of HCM is crucial for patient outcomes.
  • Electrocardiograms (ECG) offer a non-invasive method for assessing heart electrical activity.

Purpose of the Study:

  • To develop and evaluate a cardiovascular-patient classifier for identifying HCM patients.
  • To utilize standard 12-lead ECG signals for HCM detection.
  • To assess the performance of machine learning models in classifying HCM heartbeats.

Main Methods:

  • Extracted 504 morphological and temporal features from 10-second, 12-lead ECG signals.
  • Developed a classifier to identify HCM heartbeats, classifying patients based on the majority of beats.
  • Trained and tested random forest and support vector machine classifiers using 5-fold cross-validation.

Main Results:

  • Achieved patient-classification precision and F-measure close to 0.85.
  • Obtained recall (sensitivity) and specificity of approximately 0.90.
  • Demonstrated that a subset of 304 features can yield comparable performance to the full feature set.

Conclusions:

  • The developed ECG-based classifier effectively identifies patients with hypertrophic cardiomyopathy.
  • Machine learning models applied to ECG features show high diagnostic accuracy for HCM.
  • Feature selection can optimize the classifier without compromising performance, suggesting efficient diagnostic tools.

Keywords:
ElectrocardiogramFeature selectionHypertrophic CardiomyopathyPatient classificationRandom forestsSupport vector machines

More Related Videos

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

4.6K
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

9.2K

Related Concept Videos

Cardiomyopathy III: Hypertrophic Cardiomyopathy01:29

Cardiomyopathy III: Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy, or HCM, is an autosomal dominant genetic disorder characterized by asymmetric left ventricular hypertrophy without ventricular dilation. It is more common in men and is typically diagnosed in young, athletic adults.EtiologyHCM is primarily genetic and is caused by mutations in genes encoding sarcomeric proteins. Researchers have identified over 1400 mutations across at least 11 different genes. Among these, the most frequently occurring mutations are found in the...
801
Electrocardiogram01:29

Electrocardiogram

An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
9.6K
Cardiomyopathy I: Introduction and Classification01:25

Cardiomyopathy I: Introduction and Classification

Cardiomyopathy, or CMP, is a group of diseases affecting the myocardial structure, impairing its ability to pump blood effectively. This condition can lead to arrhythmias, heart failure, or sudden cardiac death.Cardiomyopathies are classified into primary and secondary categories:Primary Cardiomyopathy refers to conditions involving only the heart muscle that are often idiopathic (of unknown cause) or genetic. They primarily affect the myocardium without the involvement of other systemic...
869
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
2.1K
Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
627
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
488