基于噪声心电检测胎儿心跳的数据压缩技术综述

Bommepalli Madhava Reddy, T. Subbareddy, Saureddy Omkar Reddy, V. Elamaran
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引用次数: 5

摘要

胎儿心电图(FECG)信号为孕期及时决策提供信息。从母体腹部的复合信号中提取和检测胎儿的FECG信号对胎儿的监测任务具有重要意义。我们实现了从腹心电信号中分离脑电图信号的自适应滤波器,并了解了其性质。采用最小均方(LMS)算法实现自适应检测。为了便于存储和传输,对滤波后的心电信号进行了数据压缩技术。由于数据更为重要和敏感,因此有必要通过减少低噪声心电信号所涉及的冗余来实现高压缩比的无损压缩。这里使用快速傅立叶变换、离散余弦变换(DCT)、DCT- ii和离散正弦变换(DST)方法进行压缩。利用Matlab软件工具对压缩比、低均方百分比(PRD)等性能指标进行了比较,并将结果制成表格。
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A tutorial review on data compression with detection of fetal heart beat from noisy ECG
FECG (Fetal Electrocardiogram) signal convey information in making timely decisions during pregnancy. It is very important to extract and detect the FECG signal from a composite maternal abdominal signals for task of fetal monitoring. We implement adaptive filters for the task of separation of FECG signal from the abdominal ECG signal and understand its nature. A Least Mean Square (LMS) algorithm is implemented for the purpose of detection adaptively. Data compression techniques are implemented foe the filtered ECG signal for the purpose of easy storage and transmission. Since the data is more important and sensitive, it is necessary to implement lossless compression with high compression ratio by reducing the redundancy involved in the ECG signal with low noise. A Fast Fourier Transform, Discrete Cosine Transform (DCT), DCT-II and Discrete Sine Transform (DST) methods are used here for the purpose of compression. The performance metrics like compression ratio, low percent mean square (PRD) are compared and the results are tabulated by using Matlab software tool.
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