心室纤颤信号的自适应检测

ADAPTIVE DETECTION FOR VENTRICULAR FIBRILIATION

在分析了心室纤颤信号和心动过速信号自相关性的基础上，运用自适应ＬＭＳ算法。以误差信号能量作为特征值，成功地检测了心室纤颤信号，比仅依赖心率来判别心跳是否正常可靠性要高一些。通过对１５６个数据学习和三次判断，其心室纤颤信号识别率达到９７．４％，心动过速信号识别率达到１００％．

With the energy of the error signal (EE) as its characteristic value, Ventricular Fibrillation(VF) was successfully using adaphve LMS algorithm bed on the analysis ofautocowhtion of VF and VT (Ventricular Tachycaldin) signal. The reliability of this approachis higher than what is determined only by counting the ventricular rate. Through the learningof 156 episodes and judgements, correct identification rate of VF and VT arched 97.4%and 100% respectively.