Filter design on vlsi for EEG signals processing

Abstract : Electroencephalogram (EEG) signals are low-amplitude, non-stationary signals that are highly susceptible to noise and interference during acquisition. Efficient filtering is therefore a critical requirement for accurate EEG signal processing, especially in real-time biomedical applications. This work presents the design and implementation of a digital filter for EEG signal processing using Very Large Scale Integration (VLSI) techniques. The proposed filter architecture is optimized to remove unwanted noise components such as power-line interference and high-frequency artifacts while preserving the essential EEG signal characteristics. The filter is designed using hardware description language and synthesized for VLSI implementation with an emphasis on low power consumption, reduced area, and high processing speed. Simulation results demonstrate that the proposed design effectively enhances EEG signal quality and is suitable for real-time embedded and wearable healthcare systems. The VLSI-based approach makes the design scalable and efficient for modern biomedical signal processing applications