Team from Tampere obtained first place in Computing in Cardiology Challenge 2017The proposed method in the paper entitled “Detection of Atrial Fibrillation in ECG Hand-held Devices using a Random Forest Classifier” ranked first in this challenge.
Atrial Fibrillation (AF) is the most common cardiac arrhythmia worldwide, which is known to increase the risk of serious complications such as ischemia, stroke, and early mortality. Therefore, home monitoring of heart functioning is crucial for quick action and may decrease the chance of cardiac misdiagnosis.
In this competition, the contestants are challenged to detect Atrial Fibrillation (AF) using short electrocardiogram (ECG) recordings. 75 international teams including researchers from Philips Research North America, Philips Healthcare, University of Oxford, and EPFL have competed in the challenge.
The proposed method in the paper entitled “Detection of Atrial Fibrillation in ECG Hand-held Devices using a Random Forest Classifier” ranked first in this challenge.
The work is the result of an international collaboration among Tampere University of Technology (Doctoral student Morteza Zabihi and Prof. Moncef Gabbouj), the University of Tampere (Postdoc researcher Ali Bahrami Rad and Adj. Prof. Susanna Narkilahti) both from Finland; Northwestern University (Prof. Aggelos K. Katsaggelos) from USA, and Qatar University (Prof. Serkan Kiranyaz) from Qatar.
The same team won earlier 2nd and 3rd place in PhysioNet Challenge 2016 and IEEE NER BCI challenge 2015, respectively.