主成分分析
盲信号分离
人工智能
模式识别(心理学)
独立成分分析
计算机科学
心跳
信号(编程语言)
QRS波群
干扰(通信)
固定点算法
语音识别
医学
电信
内科学
频道(广播)
计算机安全
程序设计语言
作者
Mahesh Dembrani,K. B. Khanchandani,Anita Zurani
出处
期刊:Advances in intelligent systems and computing
日期:2017-07-13
卷期号:: 173-180
被引量:8
标识
DOI:10.1007/978-981-10-3373-5_17
摘要
Fetal electrocardiogram (FECG) gives faithful medical information of heartbeat rate of the fetal living. Extraction of FECG from abdomen of maternal woman consists of interferences and motion artifacts and noises. Maternal electrocardiogram (MECG) is a main source of interference signal present in FECG. This paper focuses on FECG extraction from blind adaptive filtering using principal component analysis (PCA). The abdominal ECG (AECG) is obtained by blind adaptive algorithm which consists of MECG and FECG QRS complex. Principal component analysis separates the two MECG and FECG. The experiments show that it can simultaneously accomplish maternal ECG and fetal QRS complexes enhancement for their detection. The simulation results show that FECG extracted from the peaks of R-R interval is noise-free signal, and extract FHR.
科研通智能强力驱动
Strongly Powered by AbleSci AI