What Is Electrocardiography?

Electrocardiography is a diagnostic technique that records the electrical activity of the heart over time by placing electrodes on the surface of the body and measuring the voltage differences that arise as cardiac muscle cells depolarize and repolarize during each heartbeat. The resulting trace, called an electrocardiogram (ECG or EKG), is a time-series waveform that encodes information about heart rate, rhythm, conduction velocity, and the integrity of the myocardium. Because the heart's electrical activity reflects its mechanical function, the ECG provides a non-invasive window into conditions ranging from benign arrhythmias to life-threatening myocardial infarction.

The technique was developed in the early twentieth century by Willem Einthoven, who described the standard bipolar limb leads and the string galvanometer used to amplify small cardiac potentials. Einthoven was awarded the Nobel Prize in Physiology or Medicine in 1924 for this work. Subsequent decades added precordial chest leads and the 12-lead configuration that remains the clinical standard today, in which ten electrodes placed on the limbs and chest yield twelve distinct views of cardiac electrical vectors.

Signal Acquisition and Lead Systems

A conventional 12-lead ECG places ten electrodes on the body: four on the limbs and six across the chest wall. These electrode pairs form twelve leads, each recording the projection of the heart's net electrical vector onto a defined axis. The three standard limb leads devised by Einthoven, designated I, II, and III, measure bipolar differences between arm and leg electrodes; the augmented limb leads (aVR, aVL, aVF) and the six precordial leads (V1 through V6) extend the spatial coverage. The standard recording duration is ten seconds, sufficient to capture several cardiac cycles at rest. Holter monitors, which record continuously for 24 to 48 hours or longer, extend this to detect intermittent arrhythmias that might not appear during a brief clinic visit. The NIH StatPearls reference on electrocardiogram basics outlines the clinical conventions for lead placement and signal interpretation.

ECG Signal Processing and Annotation

Raw ECG signals contain noise from baseline wander, powerline interference at 50 or 60 hertz, and motion artifacts from patient movement. Digital signal processing algorithms are applied to filter these artifacts before analysis. The primary waveform features extracted from a cleaned ECG are the P wave (atrial depolarization), the QRS complex (ventricular depolarization), and the T wave (ventricular repolarization). Accurate localization of these fiducial points, a task called ECG annotation, is the foundation of automated rhythm analysis. Annotation algorithms range from rule-based threshold detectors to convolutional neural networks trained on large annotated databases such as MIT-BIH and PhysioNet. The IEEE Xplore survey of ECG signal processing for cardiovascular disease recognition reviews the principal algorithmic approaches and the performance benchmarks used to evaluate them. Feature intervals derived from annotation, including the PR interval, QRS duration, and QT interval, are the primary inputs to diagnostic classifiers for arrhythmias, conduction blocks, and repolarization abnormalities.

Wearable and Ambulatory Monitoring

The miniaturization of analog front-end circuits and wireless data links has extended ECG monitoring from clinic-bound machines to wearable patches, smartwatch electrodes, and implantable loop recorders. These devices operate with fewer leads than the clinical 12-lead standard, often recording a single lead or a small number of leads, and must achieve adequate signal quality despite motion artifacts and variable electrode contact. Machine learning methods trained on population-scale datasets have improved the diagnostic accuracy of single-lead devices for conditions such as atrial fibrillation. The Nature Microsystems and Nanoengineering article on wearable ECG and PCG integration describes approaches for combining cardiac electrical and acoustic sensing in a single wearable platform.

Applications

Electrocardiography has applications in a wide range of clinical and research domains, including:

• Diagnosis and monitoring of cardiac arrhythmias, including atrial fibrillation and ventricular tachycardia
• Detection of myocardial infarction and ischemia in emergency and outpatient settings
• Assessment of drug effects and electrolyte imbalances that alter cardiac conduction
• Preoperative cardiac screening and perioperative monitoring
• Population-level cardiovascular risk assessment in epidemiological studies