Arrhythmia

Arrhythmia is a condition where the heart beats with an irregular rhythm, due to a change in the electrical impulses to the heart. These changes affect the heart’s ability to pump blood effectively, leading to other organs (i.e. lungs) becoming damaged. Arrhythmia, also known as Heart arrhythmia, dysrhythmia, or irregular heartbeat, can be categorized as follows:

Ventricular arrhythmias: Originate in the lower chambers of the heart (the ventricles): Ventricular tachycardia , Ventricular fibrillation, premature or extra heartbeat, Torsade de Pointe etc.
Supraventricular arrhythmias (or Atrial arrhythmias): Originate in the upper chambers of the heart (the atria): Atrial fibrillation, Atrial flutter, Atrial tachycardia, Paroxysmal supraventricular tachycardia etc.
Junctional arrhythmias: Originate from an ectopic focus somewhere in the atrioventricular (AV) junction.
Heart blocks: Also known as AV blocks, because most of them arise from pathology at the atrioventricular node. They are the most common causes of bradycardia.
Proarrhythmia: A new or more frequent occurrence of pre-existing arrhythmias, paradoxically precipitated by antiarrhythmic therapy, which means it is a side effect associated with the administration of some existing antiarrhythmic drugs, as well as drugs for other indications.

Related Hardware

easyTEL

Implantable telemetry

isolatedHEART

Perfusion system

emkaPACK5

Non-invasive system for large animals

rodentPACK

Jacket telemetry for rats

Electrophysiology

catheters

ecgTUNNEL

Non-invasive system for rodents

Arrhythmia detection

ecgAUTO software

ecgAUTO software is designed and constantly improved to provide:

In depth analysis of standard ECG for intervals, elevations, and areas
Automated detection of various types of arrhythmias

Minimizing time spent analyzing large volumes of ECG data, the software allows you to simultaneously perform the following analyses:

Detect subtle changes in standard parameters such as QT, PR, and others.
Detect arrhythmias and provides a summary of arrhythmia count, count by arrhythmia type and location of each arrhythmia.

Using shape recognition

Shape recognition for ECG analysis has been used in ecgAUTO for more than 15 years and has proven its reliability.

With this method, the user builds his own library of reference waveforms from scratch or start with a standard library provided by emka TECHNOLOGIES. Unrecognized ECG morphologies can easily be added to the reference library and datasets quickly reanalyzed.

Vargas, Chui and Derakhchan provided a comprehensive analysis of cardiac arrhythmias in telemetered non-naïve primates over a 6 months period. A master waveform library of arrhythmias combined with interval and rhythm changes were used to detect arrhythmias with ecgAUTO.

Waveform matching precision and priority levels

For more flexibility and efficiency, it is possible to assign different priority levels to library waveforms. This is useful for arrhythmia detection in the following ways:

High priority waveforms are used first to detect “standard” ECG complexes.
Lower priority waveforms, typically representing abnormal complexes or events, are used on signal zones that could not be analyzed in the first pass and that may contain abnormal events.

This segregation makes it possible to adapt the precision of the required shape matching algorithm either:

Independently for each waveform
According to their priority level

Combining parameters to detect arrhythmia events

ecgAUTO provides 22 types of parameters, such as interval duration, amplitude, area under the curve, preset and custom computed parameters, logical operators, etc. Each one can be used once or more in a configuration, and all are user configurable.

Combinations of parameters can be saved as templates for later use. A configuration may contain multiple such templates. For example, to detect arrhythmia, one may combine with logical operators (AND, OR) parameters that detect:

Sudden change in RR
Sudden change of any other parameter (T area for example)
Parameters that exceed preset values.
Match with a specific waveform, or subclass of waveforms.

Example:

Analysis from specific waveform shape. In the example below, a PVC is used.
False positive discrimination using amplitude, T wave area, or T-peak height.

Detecting runs

Location, count, and summary of “arrhythmia runs” can be provided by specific parameters. For instance, it is possible to detect “runs” when a class of specific waveform shapes are matched, consecutively, a minimum number of times.

Runs are represented by cluster of red dots in the lower trend graph in red. Clicking on any of these dots brings back the corresponding signals in the main screen as shown in the next graph.

Isolated p-waves

Isolated P-wave is among the events that the software can detect. They are available as one of the standard parameters, reported in a specific list and outlined on the trace.