A Decision-Making System with Reject Option for Atrial Fibrillation Prediction Without ECG Signals - 07/12/22
, D. Alshamaa a , F. Mourad-Chehade a , F. Abdallah a, b Abstract |
Objectives |
This paper presents a new method for Atrial Fibrillation detection based on the belief functions theory.
Materials and methods |
The theoretical framework allows to handle missing and uncertain data, to aggregate evidence in an independent order of sources of information and to reject a decision in case of insufficient supporting evidence. The proposed method is evaluated on real signals acquired from Intensive Care Units available in the MIMIC-III database and compared to state-of-the-art technologies and methods.
Results |
The precision of the suggested method is 90.03%, which is 2% more than existing methods in the literature.
Conclusion |
While almost all existing methods rely on high frequency sampled ECG signals, mainly at 125 Hz, to achieve a good accuracy, our proposed approach achieves a comparable performance using low frequency sampled physiological signals at 0.016 Hz without the need for an ECG which allows for a significant reduction in energy consumption, in data size and in processing complexity.
Il testo completo di questo articolo è disponibile in PDF.Graphical abstract |
Highlights |
• | An evidential decision-making system for Atrial Fibrillation prediction. |
• | Handling uncertainty and missing data. |
• | Reject decision if available data are not sufficiently informative. |
• | No use of ECG like most systems, but low frequency sampled physiological signals. |
• | Competitive performance with much less data, favoring a portable device solution. |
Keywords : Atrial fibrillation, Belief functions theory, Fusion of evidence, Decision making
Mappa
Vol 43 - N° 6
P. 573-584 - dicembre 2022 Ritorno al numero
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