An Open-Access ECG Database for Algorithm Evaluation of QRS Detection and Heart Rate Estimation
An Open-Access ECG Database for Algorithm Evaluation of QRS Detection and Heart Rate Estimation
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用于 QRS 检测和心率估计算法评估的开放式心电图数据库
DOI：
10.1166/jmihi.2019.2800
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发表时间：
2019-12-01
影响因子：
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通讯作者：
Li, Jianqing
中科院分区：
文献类型：
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作者：
Gao, Hongxiang;Liu, Chengyu;Li, Jianqing
由于信号质量较差，动态心电图（ECG）信号的R峰值检测仍然是一个挑战，这导致现有R峰值检测技术识别效率低下。当前广泛使用的开放式心电图数据库中的心电信号是在临床环境中采集的，基本上提供了高质量的心电信号。许多方法可以在这些数据库上获得较高的识别率，但如果信号质量降低，则无法正常工作。本研究提出了一个开放式心电图数据库，其中包含具有挑战性的 QRS 片段。该数据库用于第二届中国生理信号挑战赛 (CPSC 2019)，参赛者需要识别 QRS 位置，然后根据这些事件估计心率。所有批准的算法均按照 R 峰检测和 HR 估计方面定义的评分标准和规定进行评估，并以 Pan & Tompkin (P&T) 算法为基准。
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.