This paper presents a novel cardiac arrhythmia classification method based on antidictionaries. The features are sequences of consecutive slopes.
Aug 26, 2022 · Abstract— Cardiovascular diseases can be detected early by analyzing the electrocardiogram of a patient using wearable systems.
PDF | On May 28, 2022, Julien Duforest and others published Antidictionary-Based Cardiac Arrhythmia Classification For Smart ECG sensors | Find, read and cite
This paper presents a novel cardiac arrhythmia classification method based on antidictionaries, which shows an average detection accuracy of 98% while ...
Aug 25, 2022 · Abstract— Cardiovascular diseases can be detected early by analyzing the electrocardiogram of a patient using wearable systems.
This paper presents a novel cardiac arrhythmia classification method based on antidictionaries. The features are sequences of consecutive slopes generated from ...
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May 28, 2022 · This paper presents a novel cardiac arrhythmia classification method based on antidictionaries. The features are sequences of consecutive slopes ...
Jun 2, 2024 · In this article, non-uniformly sampled electrocardiogram (ECG) signals obtained from level-crossing analog-to-digital converters (LC-ADCs) are ...
Antidictionary-based cardiac arrhythmia classification for smart ECG sensors ... Slope-based event-driven feature extraction for cardiac arrhythmia classification.
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One approach is to use antidictionaries, which are sequences of consecutive slopes generated from the input signal's event-driven processing [??]. This method ...