FPGA based ECG analysis system

electronics and instrumentation engineering

This paper presents a proposed design for analyzing electrocardiography (ECG) signals. This methodology employs adaptive filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Cosine Transform (DCT) 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 Spartan 6 Field Programming Gate Array (FPGA) board. We have compared discrete wavelet transform (DWT) with discrete cosine transform (DCT) as feature extraction methodology in simulation. Adaptive filters self learn. As the signal into the filter continues, the adaptive filter coefficients adjust themselves to achieve the desired result, such as identifying an unknown filter or canceling noise in the input signal. Adaptive filter is mainly used for ECG since the signals are very feeble..We have simulated both the systems one using DCT and other using DWT and studied the area occupied in SYSTEM GENERATOR mat lab R2013a. .For the real time analysis we have dumped the DCT system coding done in ISE design suit 14.5.

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