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This paper is in the following e-collection/theme issue:

Advanced Data Analytics in eHealth (341) Wearable Devices and Sensors (1544) Novel Sensors and Data Acquisition Methods in Cardiology (256) Artificial Intelligence (4590) Cardiac Arrhythmia, Atrial Fibrillation (140)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91960, first published .
2D-CNN model analyzes ECG R-peak data to classify Non-AF, AF, and noise.

R-R Interval Histogram-Based Deep Learning for 3-Class Atrial Fibrillation Screening in Garment-Type Wearable Holter Electrocardiogram Monitoring: Algorithm Development and Validation Study

R-R Interval Histogram-Based Deep Learning for 3-Class Atrial Fibrillation Screening in Garment-Type Wearable Holter Electrocardiogram Monitoring: Algorithm Development and Validation Study

Authors of this article:

Tomoaki Nakano1 Author Orcid Image ;   Keita Okayama1 Author Orcid Image ;   Masanao Yasuoka2 Author Orcid Image ;   Hironori Shigeta2 Author Orcid Image ;   Akito Kawamura1 Author Orcid Image ;   Takayuki Sekihara1 Author Orcid Image ;   Kentaro Ozu1 Author Orcid Image ;   Takafumi Oka1 Author Orcid Image ;   Shigeto Seno2 Author Orcid Image ;   Yasushi Sakata1 Author Orcid Image
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