期刊
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
卷 9, 期 9, 页码 1853-1858出版社
AMER SCIENTIFIC PUBLISHERS
DOI: 10.1166/jmihi.2019.2800
关键词
Electrocardiogram (ECG); QRS Detection; Heart Rate (HR); Database; CPSC
资金
- National Natural Science Foundation of China [81871444]
- Key Research and Development Programs of Jiangsu Province [BE2017735]
- ICBEB
- State Key Laboratory of Bioelectronics in China
- Southeast-Lenovo Wearable Heart-Sleep-Emotion Intelligent monitoring Lab
R-peak detection for dynamic electrocardiogram (ECG) signal is still a challenge due to the poor signal quality, which leads to inefficient recognition of the existing R-peak detection technologies. Collected in clinical environment, ECG signals from current widely-used open-access ECG databases are basically provided with high quality. Many methods can achieve high recognition rate on these databases but fail to work properly if the signal quality reduces. This study presents an open-access ECG database comprises of challenging QRS segments. The database is used for the 2nd China Physiological Signal Challenge (CPSC 2019), where participants are expected to identify QRS locations and then estimate HR from these, episodes. All the approved algorithms are evaluated by scoring standards and regulations defined in terms of both R-peak detection and HR estimation, with Pan & Tompkin (P&T) algorithm as a benchmark.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据