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 follow:
- Ventricular arrhythmias: Originate in the lower chambers of the heart (the ventricles)
- Atrial arrhythmias: Originate in the upper chambers of the heart (the atria)
- Junctional arrhythmias : Originate from an ectopic focus somewhere in the atrioventricular (AV) junction.
- Heart blocks: Also known as AV blocks, because the vast majority 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.
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
The goal is to minimizes time spent on large volumes of ECG data from which one wishes, from a single analysis run, to simultaneously :
- 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 can build his own library of reference waveforms from scratch or start with a standard library provided by emka TECHNOLOGIES. If the software fails to analyze because the morphology of ECG is not matched by any shape, it is simple and fast to add it to the reference library.
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 in detection of 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:
- 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 parameter, logical operators, etc.
Each one can be used once or more in a configuration and all are user configurable.
Combination 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.
- 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
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 bring back the corresponding signals in the main screen as shown in the next graph.
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.
Implants for large animals
Implants for rats
ecgAUTO, post-processing software
Inhalation of printer-emitted particles impairs cardiac conduction, hemodynamics, and autonomic regulation and induces arrhythmia and electrical remodeling in rats
Alex P. Carll et al, Particle and Fibre Toxicology (2020)
Effect of genetic background on the cardiac phenotype in a mouse model of Emery-Dreifuss muscular dystrophy
Nicolas Vignier et al, Biochemistry and Biophysics Reports Volume 19, 2019
Inhaled ambient-level traffic-derived particulates decrease cardiac vagal influence and baroreflexes and increase arrhythmia in a rat model of metabolic syndrome
Carll et al, Particle and Fibre Toxicology, 2017
Comprehensive analysis of cardiac arrhythmias in telemetered cynomolgus monkeys over a 6 month period
Ray W. Chui et al, Journal of Pharmacological and Toxicological Methods, 2012