FPGA-based electrocardiography (ECG) signal analysis system using least-square linear phase finite impulse response (FIR) filter

This paper presents a proposed design for analyzing electrocardiography (ECG) signals. This methodology employs highpass least-square linear phase Finite Impulse Response (FIR) filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Wavele...

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Bibliographic Details
Main Authors: Mohamed G. Egila, Magdy A. El-Moursy, Adel E. El-Hennawy, Hamed A. El-Simary, Amal Zaki
Format: Article
Language:English
Published: SpringerOpen 2016-12-01
Series:Journal of Electrical Systems and Information Technology
Subjects:
DSP
Online Access:http://www.sciencedirect.com/science/article/pii/S2314717216300125
Description
Summary:This paper presents a proposed design for analyzing electrocardiography (ECG) signals. This methodology employs highpass least-square linear phase Finite Impulse Response (FIR) filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Wavelet Transform (DWT) was utilized as a feature extraction methodology to extract the reduced feature set from the input ECG signal. The design uses back propagation neural network classifier to classify the input ECG signal. The system is implemented on Xilinx 3AN-XC3S700AN Field Programming Gate Array (FPGA) board. A system simulation has been done. The design is compared with some other designs achieving total accuracy of 97.8%, and achieving reduction in utilizing resources on FPGA implementation.
ISSN:2314-7172