Cardiac Analysis

Advanced ECG analysis software

Cardiolund provides state-of-the-art software for analysis of cardiac databases and cardiac devices.

Software for automated parsing and rhythm analysis of ECGs

Cardiolund creates remarkable ECG analysis software based on decades of research and development. Our core product, the ECG Parser, includes some of the world's most advanced algorithms for cardiac signal analysis. Our software is integrated with a range of different ECG systems, and is also used in numerous clinical research studies.

The algorithms can handle from 1 to 12 leads of ECG data, and are particularly well-suited for identification of rhythm deviations in recordings from simplified ECG systems, such as single lead recordings from mobile devices, and Holter systems.

Atrial fibrillation (AF) screening performance of the ECG Parser has been evaluated in a large clinical study, involving more than 80 000 thumb-ECGs recorded in participant's own home. In this study, Cardiolund's ECG Parser correctly identified all patients with AF. The software also provided a close to 90% workload reduction, by focusing the physician's attention on the important cases, when trying to find AF episodes in the data.

The ECG Parser provides a detailed set of descriptors and a categorisation for each sample segment. The rich meta data produced by the analysis are useful for both long term monitoring and screening purposes, and for a variety post-processing applications, such as statistical analysis, machine learning or AI based decision support systems.

When intergrating the ECG Parser with a medical system, a custom results data viewer, or a report generator, can be created to summarise the information in a format suitable for clinical interpretation by a physician. The ECG Parser software can also serve as analysis backend for a custom device user interface.

For large databases of recordings, the analysis results can be used to provide swift guidance for physicians, by highlighting the important cases or intervals. The detailed signal descriptors can also be used for searching, segmenting and filtering ECGs when investigating disease progression for a single patient, or across large patient groups.


Application areas for automatic ECG analysis software

ECG System Providers

Healthcare Organisations

Researchers

Clinicians and Consumers