Implementation of optimized technique for enhancing EEG signal Quality by improving Signal to Noise Ratio

Optimized technique for enhancing EEG signal quality by improving the signal-to-noise ratio (SNR). EEG signals are inherently noisy due to various factors, such as the presence of biological and environmental artifacts, and low amplitude of brain signals. The proposed technique involves the application of advanced signal processing algorithms, including wavelet denoising, independent component analysis (ICA), and adaptive filtering. These algorithms are applied sequentially to reduce noise and improve the SNR of EEG signals. The proposed technique was tested on real EEG data and showed a significant improvement in the quality of the EEG signals. The results demonstrate that the optimized technique can effectively enhance the SNR of EEG signals and improve their quality, which could have important implications in clinical and research applications of EEG.