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Determination Of The Causality Score Of Atrial Fibrillation

Technology Overview

Despite advances in arrhythmia treatment technology, atrial fibrillation (AF) remains a worldwide cardiovascular epidemic affecting more than 33 million individuals globally. AF carries a 5-fold increased risk of brain stroke, 3-fold increased risk of heart failure and causes up to 40% of annual hospitalizations of AF patients. For these reasons, AF imposes a substantial economic burden, e.g., the total healthcare costs of AF reach 2.6% of healthcare expenditure in Europe.

The present invention relates to methods for assessment of a person’s health risks based on the person’s biosignals, and more particularly, to a method for establishing a causality score between person’s atrial fibrillation triggers and atrial fibrillation pattern. The causality score might be useful in nonpharmacological self-management of the disease in its early stages by inspiring lifestyle behaviour changes.

Technology Features, Specifications and Advantages

The present invention provides a method for establishing a causality score between person’s AF triggers (e.g., alcohol, caffeine, physical exertion) and a person’s temporal AF episode occurrence pattern which may comprise of a single self-terminating AF episode, several episodes, a cluster, or several clusters of AF episodes. The personal computing device is responsible for collecting and pre-processing of the data, transmitting the data to the cloud server and presenting the results of analysis. The cloud-based server stores, synchronises, and analyses the data collected. Finally, it sends the results of analysis back to the personal computing device. The method comprises producing temporal AF episode occurrence patterns from continuously monitored biosignals, detecting AF triggers in biosignals, enrolling data representing person-reported AF triggers, transforming the data representing reported AF triggers to time-series signals, matching the time-series signals with the temporal AF episode occurrence pattern, calculating a causality score between the suspected AF triggers and the temporal AF episode occurrence pattern.

Potential Applications

The market segment which benefits most from the invention is patients with diagnosed paroxysmal AF. AF has been diagnosed in 33 million people worldwide, but the true prevalence due to asymptomatic cases may be much higher.

The treatment of AF is particularly costly, with the US having an annual cost of $ 26 billion for AF. AF is a disease of the elderly (> 65 years), so the prevalence of AF is projected to increase up to 3-fold in the coming decades due to an aging population.

Potential users and buyers can be:

  • Private treatment facilities that could provide atrial arrhythmia monitoring and arrhythmia management services to their patients.
  • Patients with severe disease (stroke, myocardial infarction) at increased risk of developing AF.

Customer Benefit

  • With an AF management service, patients will have a better understanding of individual AF provoking factors.
  • Patients will receive instructions on the necessary lifestyle changes to manage the disease more effectively and feel responsible for actively participating in improving the quality of life.
  • The developed technology will promote the development of telemedicine services. AF patients will be provided with wearable devices and software that will inform medical providers about AF triggers, the progress of AF management, and the effectiveness of medication.
Contact Person

Julija Kravčenko


Kaunas University of Technology

Technology Category

  • Healthcare
  • Telehealth, Medical Software & Imaging

Technology Readiness Level


Atrial fibrillation, Health risk, Causality score, Biosignals, Atrial fibrillation triggers, Atrial fibrillation pattern