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The ECG (Electrocardiogram) signal is the most important signal in the biomedical signal processing, because it is used to diagnose the wellness of heart’s activity. Now a days the ECG signal processing devices have become more compact and smaller in size. Implementing the algorithms in devices is a complex task. Various blocks like preprocessing, extraction and diagnosis have to be implemented in hardware. The ECG signal will be corrupted by different types of noises. The filter to be implemented should be efficient in removal of the noise and extraction of medical information. In this paper, implementation of adaptive filtering using Swarm-based optimization techniques for biomedical system on chip architecture is presented. The proposed algorithm was implemented in different hardware and the performance is compared. The filters show linear phase and high rejection ratio. Field programmable gate arrays were used for implementation. These adaptive filters form the part of filter circuits for preprocessing and extraction of ECG signals. Implementation was done using Intel Altera innovative Programmable Power Technology tool Quartus.

Swarm Intelligence-based Optimized Adaptive Filtering Technique for ECG Data Analysis System