Lin Chia-Hung, Du Yi-Chun, Chen Yung-Fu, Chen Tain-Song
Dept. of Electr. Eng., Kao-Yuan Univ., Kaohsiung 821, Taiwan.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:2154-8. doi: 10.1109/IEMBS.2006.260019.
This paper proposes a method for multiple ECG beats recognition using novel grey relational analysis (GRA). Converts each QRS complex to a Fourier spectrum from ECG signals, the spectrum varies with the rhythm origin and conduction path. The variations of power spectra are observed in the range of 0 Hz-20 Hz in the frequency domain. According to the frequency-domain parameters, GRA performs to recognize the cardiac arrhythmias including the supraventricular ectopic beat, bundle branch ectopic beat, ventricular ectopic beat, and fusion beat. The method was tested on MIT-BIH arrhythmia database. The results demonstrate the efficiency of the proposed non-invasive method, and also show high accuracy for detecting electrocardiogram (ECG) signals.
本文提出了一种使用新型灰色关联分析（GRA）进行多心电图搏动识别的方法。将每个QRS复合波从心电图信号转换为傅里叶频谱，该频谱随节律起源和传导路径而变化。在频域中观察到功率谱在0 Hz - 20 Hz范围内的变化。根据频域参数，GRA用于识别心律失常，包括室上性异位搏动、束支异位搏动、室性异位搏动和融合搏动。该方法在MIT - BIH心律失常数据库上进行了测试。结果证明了所提出的非侵入性方法的有效性，并且在检测心电图（ECG）信号方面也显示出高精度。
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