噪音(视频)
信号(编程语言)
计算机科学
离散余弦变换
均方误差
语音识别
均方根
信噪比(成像)
滤波器(信号处理)
小波
人工智能
数学
模式识别(心理学)
计算机视觉
统计
电信
工程类
图像(数学)
电气工程
程序设计语言
作者
Ali Ukasha,Mohammed Omar,Mai Fadel
标识
DOI:10.1109/iecres57315.2023.10209428
摘要
An electrocardiogram (ECG) signal is a representation of the electrical activity generated by the heart muscles that is primarily used to detect heart abnormalities. Due to the sensitive nature of the ECG, it contains many types of noise such as baseline wandering, powerline interference, EMG signal, and electrode motion artifacts. This paper introduces a simple signal processing techniques to remove baseline wandering noise from ECG signal. Baseline wandering is a low-frequency noise ranging from 0.5 to 0.6 Hz. This paper proposes a Notch filter and an orthogonal wavelet family by Daubechies families to reduce baseline wandering from the ECG signal. In this work, the ECG compression is based on discrete cosine transform (DCT) and Run Length Encoding (RLE). A comparative study for system performance of the ECG signal in terms of compression ratio (CR), percentage root mean square difference (PRD), mean square error (MSE), and peak-signal-to-noise ratio (PSNR). The results showed that only 12% of the DCT coefficients after the compression process are used to reconstruct the ECG signal, with a compression ratio up to 8.6957 by using (RLE) encoding. Percentage root mean square difference is 0.1436 (PRD) after filtering the signal with a low-pass FIR at the PSNR is equal to 31. 0157dB at the end point of the receiver.
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