摘要
为弥补房颤诊断中不能通过心跳节律确诊的缺陷,提出一种基于高斯模型的识别心电信号(electrocardiogram,ECG)中P波的策略。针对实际病患的P波形态的多样性,分别建立3类P波的高斯混合模型(Gaussian mixture model,GMM),利用马氏距离(Mahalanobis distance,MD)统计出P波的阈值边界,利用窗口滑动方法获取ECG时间段波形,进行高斯模型计算,其结果与3类P波高斯模型比较,从而识别P波。采用MIT-BIH中的Atrial Fibrillation Database为实验数据进行测试,实验结果表明,圆滑P波、尖耸P波、双峰P波以及水平直线波形的识别准确率分别为80.50%、84.36%、67%和100%,验证了模型和算法的可行性。
To make up for the defects that heartbeat rhythm can not be used as evidence to atrial fibrillation diagnosis, a strategy based on Gaussian model to identify P wave in electrocardiogram (ECG) was proposed. According to the diversity of P wave patterns of actual patients, three kinds of P-wave Gaussian mixture model (GMM) were established, and the threshold of P wave was calculated using Mahalanobis distance (MD). The sliding method was used to acquire the waveform of the ECG time period and to perform Gaussian model calculation. The results were compared with that of the three types of P-wave Gaussian models to identify the P-wave. Experimental data were tested using Atrial Fibrillation Database in MIT-BIH. Experimental results show that the recognition accuracy of smooth P wave, sharp P wave, double peak P wave and horizontal straight line waveform are 80.50%, 84.36%, 67%, and 100% respectively, verifying the feasibility of the model and algorithm.
作者
郑刚
王贺贺
ZHENG Gang;WANG He-he(School of Computer Science and Engineering,Tianjin University of Technology,Tianjin 300384,China)
出处
《计算机工程与设计》
北大核心
2019年第6期1713-1717,共5页
Computer Engineering and Design
基金
天津市自然科学基金项目(16JCYBJC15300)
关键词
心电信号
心房颤动
P波高斯模型
马氏距离
高斯混合模型
electrocardiogram(ECG)
atrial fibrillation(AF)
P wave Gaussion model
Mahalanobis distance(MD)
Gaussian mixture model (GMM)
