A new study that reports on the clinical performance of the Cardiolund ECG Parser has been published: Åke Olsson, Symptom-Ruled Real World Arrhythmic Recordings With an Internet Based System, Circulation 2018;138:A12893.
A new major version 2.0 of the Cardiolund ECG Parser is released today. The focus of this release is on improving the specificity of the review groups used in atrial fibrillation (AF) screening of large databases with home based thumb-ECG recordings.
The Swedish Governmental Agency for Innovation Systems (Vinnova) has awarded a research grant) of 1.2 million SEK to a project partnership between Cardiolund, Coala Life and Region Gävleborg.
We are consolidating our business, and will move forward with a more concise company name: “Cardiolund Research AB” is now “Cardiolund AB”.
Cardiolund have completed the ISO 13485 compliance assessment, and we now have a fully certified quality management system for developing medical device software. We have also CE marked the ECG Parser (and associated products). It is now certified as a Class IIa medical software for automated rhythm analysis of ECGs.
There is a growing interest in identifying AF patients at an early stage to be able to intervene the progression of the condition and to prevent stroke cases. Identifying AF patients may be complicated by factors such as AF being without symptoms (silent AF) for many patients, and the variety of non-critical arrhythmia that are found in ECGs in an ageing population.
There are multiple challenges when it comes to detection of atrial fibrillation (AF) in simplified home-based ECG measurements. In Cardiolund Research we create software algorithms that overcome these challenges, and enables automatic ECG analysis of simplified home-based measurements, for screening purposes.
The Swedish newspaper Sydsvenskan has today published an article about Cardiolund (in Swedish). The same article is also printed on the economy pages of today’s edition of the newspaper, see photo below.
The atrial fibrillatory rate (AFR) is an exciting topic that I’ve had the opportunity to research on over the last two decades, in my work with algorithms for signal processing of ECGs. Today we have a state-of-the-art algorithm for calculating atrial fibrillatory rate, which has important use cases in the prediction of spontaneous AF termination, or termination induced by DC conversion, anti-arrhythmic drugs and ablation procedures.
We have built a powerful software tool we call the ECG Parser. This software transforms an ECG signal, or an entire database of ECG signals, into a very detailed description of the content.