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

Abstract

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.

Keywords

• Electrocardiography (ECG)
• Discrete wavelet transform (DWT)
• FPGA
• DSP
• Bio-medical applications