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What is EEG-Based Stroke Severity Classification about?

This study evaluates stroke severity using a first-order multilayer neural network with EEG data, focusing on acute ischaemic stroke (AIS). The proposed method achieves a high accuracy of 97.3% by analyzing power spectral density (PSD) from EEG recordings, categorizing strokes into normal, mild, moderate, and severe classes. The research highlights the advantages of using EEG over traditional imaging techniques, emphasizing its cost-effectiveness and quicker diagnostic capabilities.

Author

Bhuvana Madhu

Language

EN