SHDB-AF: a Japanese Holter ECG database of atrial fibrillation
arxiv(2024)
摘要
Atrial fibrillation (AF) is a common atrial arrhythmia that impairs quality
of life and causes embolic stroke, heart failure and other complications.
Recent advancements in machine learning (ML) and deep learning (DL) have shown
potential for enhancing diagnostic accuracy. It is essential for DL models to
be robust and generalizable across variations in ethnicity, age, sex, and other
factors. Although a number of ECG database have been made available to the
research community, none includes a Japanese population sample. Saitama Heart
Database Atrial Fibrillation (SHDB-AF) is a novel open-sourced Holter ECG
database from Japan, containing data from 100 unique patients with paroxysmal
AF. Each record in SHDB-AF is 24 hours long and sampled at 200 Hz, totaling 24
million seconds of ECG data.
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