Afonso V X, Tompkins W J, Nguyen T Q, Luo S
Endocardial Solutions, Inc., Saint Paul, MN 55108, USA.
IEEE Trans Biomed Eng. 1999 Feb;46(2):192-202. doi: 10.1109/10.740882.
We have designed a multirate digital signal processing algorithm to detect heart beats in the electrocardiogram (ECG). The algorithm incorporates a filter bank (FB) which decomposes the ECG into subbands with uniform frequency bandwidths. The FB-based algorithm enables independent time and frequency analysis to be performed on a signal. Features computed from a set of the subbands and a heuristic detection strategy are used to fuse decisions from multiple one-channel beat detection algorithms. The overall beat detection algorithm has a sensitivity of 99.59% and a positive predictivity of 99.56% against the MIT/BIH database. Furthermore this is a real-time algorithm since its beat detection latency is minimal. The FB-based beat detection algorithm also inherently lends itself to a computationally efficient structure since the detection logic operates at the subband rate. The FB-based structure is potentially useful for performing multiple ECG processing tasks using one set of preprocessing filters.
我们设计了一种多速率数字信号处理算法来检测心电图（ECG）中的心跳。该算法包含一个滤波器组（FB），它将心电图分解为具有均匀频率带宽的子带。基于FB的算法能够对信号进行独立的时间和频率分析。从一组子带计算出的特征和一种启发式检测策略被用于融合来自多个单通道心跳检测算法的决策。针对麻省理工学院/贝斯以色列女执事医疗中心（MIT/BIH）数据库，整体心跳检测算法的灵敏度为99.59%，阳性预测值为99.56%。此外，这是一种实时算法，因为其心跳检测延迟最小。基于FB的心跳检测算法由于检测逻辑以子带速率运行，其本身也适合采用计算效率高的结构。基于FB的结构对于使用一组预处理滤波器执行多个心电图处理任务可能很有用。
