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Journal Article

An Open-Access Arrhythmia Database of Wearable Electrocardiogram

Qin Shen; Hongxiang Gao; Yuwen Li; Qi Sun; Minglong Chen; Jianqing Li; Chengyu Liu
Journal of Medical and Biological Engineering · Vol. 40, Issue 4 · pp. 564-574 · 2020

Abstract

Purpose Heart arrhythmias result from any disturbance in the rate, regularity, and site of origin or conduction of the cardiac electric pulse. Sporadic and underappreciated characteristics make diagnosis less timely, leading to stroke, heart failure, or even sudden death. Wearable electrocardiogram (ECG) devices are gradually becoming the main trend of intelligent diagnosis alongside the improvement of information transmission and computation power of the hardware. Therefore, a database for arrhythmia detection was planned to construct. Methods Collaborating with hospital, this study presents a bipolar limb two-lead wearable device by collecting a large amount of real-time data and giving rise to readily available ECG databases. Results In total, the database contains 2000 30-s recordings of sinus, atrial and ventricular arrhythmias collected from more than 200 voluntary patients who had been diagnosed with heart diseases, ranging in age from 18 to 82. Meanwhile, manual annotations by cardiologists were proposed to benefit and instruct non-medical researchers to design the algorithm reasonably.

Bibliographic Information

JournalJournal of Medical and Biological Engineering
PublisherSpringer
Publication Date2020-08-01
Publication Year2020
Volume40
Issue4
Pages564-574
Document TypeJournal Article
Print ISSN1609-0985
eISSN2199-4757
DOI10.1007/s40846-020-00554-3

Access Information

NARA Access Coverage2015-01-01~Current
Journal Homepagehttps://www.springer.com/journal/40846
Publisher PageOpen Publisher Page
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