Key result
FPGA-based digital filters attenuate ECG noise, improving average signal-to-noise ratio by ~8 dB.
Why the study?
ECG signals are often contaminated by noise leading to misinterpretation of heart disease, making denoising essential for accurate assessment of heart health.
An FPGA-based composite digital filter successfully attenuates noise in ECG signals, improving signal-to-noise ratio with low power consumption and resource utilization.
The Electrocardiogram (ECG) is a graphical representation of the electrical activity of the heart that is captured through a non‐invasive process and is used to monitor the state of the heart. Because of its low power, ECG signal is often contaminated with different types of noises. Noisy ECG recording often leads to misinterpretation of heart disease. Hence, denoising of ECG signal is utmost important for accurate assessment of heart health. Addressing this issue, the paper presents a real‐time composite digital filter model that attenuates noise from a corrupted ECG signal. The proposed model integrates three classical digital filters: an elliptic high pass infinite impulse response (IIR) filter, moving average (MA) type finite impulse response (FIR) low pass filter, and IIR elliptic band stop filter. All filters are realized using transposed structure and implemented on FPGA platform. The soft model is developed through graphical programing in MATLAB Simulink by using only basic Xilinx System Generator (XSG) blocks and is emulated in Zedboard Zynq‐7000 FPGA board. For hardware emulation of the model, 2.61% of total available resource is utilized and 0.278 W on‐chip power is consumed. The Worst Negative Slack (WNS) for our design is 2.789 ns, indicating that it meets all required time constraints and the hardware implementation of the soft design is successful on the FPGA board. The model is tested using 376 ECG recordings from the MIT‐BIH Normal Sinus Rhythm, MIT‐BIH Arrhythmia, and ECG‐ID databases. Additionally, we have introduced various noise signals from the MIT‐BIH Noise Stress Test database and synthetically generated in MATLAB to further corrupt the ECG signals. The average improvement in signal‐to‐noise ratio (SNR imp ) achieved by our model is 7.61 dB for the ECG‐ID database, 6.9 dB for the MIT‐BIH Arrhythmia database, and 8.42 dB for the MIT‐BIH Normal Sinus Rhythm database. The average root mean square error (RMSE) values are 0.0975, 0.2616, and 0.2168, and the average percentage root mean square difference (%PRD) values are 77.91, 64.11, and 68.21 are computed, respectively.
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Saha et al. (2026) studied ECG noises (n=376). FPGA-based composite digital filter was evaluated on Signal-to-noise ratio improvement (SNR imp). An FPGA-based composite digital filter successfully attenuated noise from corrupted ECG signals, achieving an average signal-to-noise ratio improvement of 6.9 to 8.42 dB across various databases.
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