Modified Block Sparse Bayesian Learning-Based Compressive Sensing Scheme for EEG Signals

Advancement in medical technology creates some issues related to data transmission as well storage. In real-time processing, it is too tedious limit the flow of may reduce meaningful information too. So, an efficient technique required compress data. This problem arises Magnetic Resonance Imaging (MRI), Electro Cardio Gram (ECG), Electroencephalogram (EEG), and other signal processing domains. this paper, we demonstrate Block Sparse Bayesian Learning (BSBL) based compressive sensing on (EEG) signal. The efficiency algorithm described using Mean Square Error (MSE) Structural Similarity Index Measure (SSIM) value. Apart from analysis also use different combinations matrices too, effect MSE SSIM And here got that exponential chi-square random a matrix are showing significant change value SSIM. body sensor networks, scheme will contribute reduction power requirement due its compression ability cost size device used for monitoring.