GAO Li-kun, LIU Dong-qi, CHEN Zhi-jian. Real-time ECG signal extraction algorithm based on correlation evaluation and FastICA[J]. 2018, (8): 112-115. DOI: 10.13873/j.1000-9787(2018)08-0112-04.
基于相关性评估与FastICA的实时心电信号提取算法
摘要
针对传统的独立成分分析(ICA)算法无法实现实时的信号分离和提取的问题
提出一种基于相关性评估和实时Fast ICA的方法。通过对混合信号分段
并进行Fast ICA处理
再对分离后的信号段进行相关性评估
选取与心电信号相关性最大的信号段进行相位的修正与幅值缩放
实现心电(ECG)信号的实时提取。在分离处理前
对混合信号进行基线漂移的过滤
提高了算法的鲁棒性。实验表明:所提算法的准确率可达96.7%
能够有效实现心电信号的实时提取。
Abstract
Aiming at problem that traditional independent component analysis( ICA) algorithm can’t realize realtime separation and extraction of signal
an algorithm based on correlation evaluation and realtime Fast ICA is proposed. The algorithm divides mixed signal into signal segments and Fast ICA processing is carried out
and conducts correlation evaluation on signal segment. The separated signal segment which is most correlated to electrocardiogram( ECG) signal is selected for phase modification and amplitude zoom to realize ECG signal realtime extraction. Baseline drift removing of mixed signal is carried out before separating processing
improve robustness of agorithm. Experimental results demonstrate that accuracy of the proposed algorithm can achieve 96.7%
can realize real-time extraction of ECG signal effectively.