摘要
提出了一种引入异常心电节律分析的房性早搏识别算法。算法通过心拍模板分析识别QRS波形态,并依据心率和心电图特征识别异常节律。经MIT-BIH心律失常数据库检验,算法对于房性早搏的特异度和灵敏度分别达到了99.5%和96.9%。
In this paper,an algorithm for atrial premature beat classification with abnormal ECG rhythm analysis is presented. The classification algorithm identifies QRS morphology by template matching and recognizes abnormal ECG rhythm by the features of heart rate and ECG.Algorithm has been evaluated by the MIT-BIH arrhythmia database and the results show that the specificity and the sensitivity for atrial premature beat are 99.5%and 96.9%respectively.
出处
《中国医疗器械杂志》
CAS
2008年第5期313-315,340,共4页
Chinese Journal of Medical Instrumentation
基金
国家"十一五"科技支撑项目(2007BAI07A28)
浙江省科技攻关计划重点项目(2007C21079)
关键词
房性早搏
心律失常
心拍分类
atrial premature
arrhythmia
beat classification
