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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.
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:
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 also available.
*Video-electroencephalogram
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 shape 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:
Did you know?
ecgAUTO can perform a concurrent interval and arrhythmia analysis, eliminating the need for multiple analyses of a single data file.
Load, analyze, and export large data files in minutes.
Interval and Arryhthmia Analysis: 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.
Manually mark and qualify events, such as arrhythmia for example, according to a predefined list of labels.
To comply with regulatory requirements, optional GLP modules can be activated on ecgAUTO software. Data consistency, reliability and integrity are ensured by:
User management: The usersMANAGEMENT module controls the access rights by login and password. Access rights are characterized by a level (e.g. simple user, administrator) with an optional expiry date and a logout period.
Audit trail: auditCENTRAL software collects audit lines sent to Windows event logs of all client computers and keep them into a database. Each entry in the audit trail contains a list of all actions done on emka TECHNOLOGIES programs that affect or potentially affect raw or processed data, such as the date and time of the action, the user who performed the action or the computer on which the action was performed.
Electronic signature: The eSIGN module offers encrypted electronic signatures.
Study management: This module associates data files to a study.
To comply with SEND requirements, ecgAUTO generates SEND 3.1 compatible tables that can easily be exported to .xls, .csv and integrated into third-party solutions by Instem and Xybion to increase productivity in preclinical studies.
The events edit option allows to manually mark and qualify events, such as arrhythmia for example, according to the SEND terminology.
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.
“The autonomy to adjust fiduciary points of the library waveforms for pattern recognition in ECG analysis sets ecgAUTO apart from competing software. The software can handle large datasets with multiple physiological signals per file as well.“
Dr. Alex Carll, University of Louiseville.
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