ecgAUTO, post-processing software

ecgAUTO is an in-depth cardiovascular analysis software.
From multiple species or leads, it uses shape recognition techniques for interval analysis, arrhythmia detection, heart rate variability, blood pressure assessment, etc.
Features include customizable parameters and protocols, interactive dashboards, batch analysis, comprehensive data reports, and more.
Optional GLP modules and SEND formatted exports are also available.
Add-on modules for neurological and respiratory analysis create a single analysis platform for interdisciplinary studies.
Benefits
Modular
Efficient
Customizable
Description
Modular
ecgAUTO modular design allows you to implement only the needed analysis tools.
Simple modules like RR analysis, blood pressure or blood flow assessment can be used in stand-alone, or combined with additional modules, for advanced analysis:
- in-depth interval analysis
- arrhythmia detection
- heart rate variability
- baroreflex sensitivity
- isolated P wave detection
Add-on modules for neurological and respiratory endpoints can be combined for multi-disciplinary studies.
Additional modules for importation of non-EMKA files as well as GLP modules, SEND formatted exports, and vEEG* are available.
*Video-electroencephalogram


Efficient analysis
In-depth ECG analysis is at the heart of ecgAUTO software.
Using the pioneering shape recognition techniques, ecgAUTO is able to analyze normal or abnormal ECG morphology, from any species and any lead.
The pattern recognition technique requires a library of reference waveforms, built and edited by the user. Specific libraries can be built for different species or leads, which make the strength of this technique.
Several days of manual analysis are turned into a few minutes of automated analysis with ecgAUTO software:
- Load, analyze, and export large data files in minutes.
- As an example, a two-weeks study analyzed manually in tree days is processed in 30 minutes
- Concurrent interval and arrhythmia analysis eliminates the need for multiple analyses of a single data file.
- Automated isolated P wave detection dramatically decreases the time spent overreading data. Statistics on occurrences per data zone are automatically produced.

Customizable
Standard or custom parameters and protocols are used in analysis and for the production of comprehensive data reports. Interactive dashboards (i.e. multi trend graph, XY plot, Poincaré plot) can be utilized to QA/QC your data on the fly.
Perform batch analysis with custom configurations on a per file and per subject basis.
Alex Carll’s interview
In an interview, Alex Carll, from the University of Louisville, explains how he uses ecgAUTO software to analyze ECG, blood pressure, and left ventricular pressure in rodents.
Alex Carll studies the biological mechanisms by which air pollutants weaken the heart, impair cardiac conduction, and compromise hemodynamics, and whether such effects occur through the autonomic nervous system.
Applications
And more!
Related publications
The in vivo QTc core assay: An evaluation of QTc variability, detection sensitivity and implications for the improvement of conscious dog and non-human primate telemetry studies
J. Baublits et al. Journal of Pharmacological and Toxicological Methods. 2021
Women's Cardiovascular Risk from PM Exposure: A Laboratory-based Toxicology Study Using a Sensitive Animal Model
Michael T. Kleinman et al, Report from 2020.
Comprehensive multilevel in vivo and in vitro analysis of heart rate fluctuations in mice by ECG telemetry and electrophysiology
Stefanie Fenske et al, Nature protocols, 2015
Involvement of peroxisome proliferator-activated receptors in cardiac and vascular remodeling in a novel minipig model of insulin resistance and atherosclerosis induced by consumption of a high-fat/cholesterol diet
Pan Yongming et al, Cardiovascular Diabetology 2015
Heart rate variability in mice: a theoretical and practical guide
Thireau et al, Experimental Physiology, 2008
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