AI tekniği ve IoTs kullanılarak EEG sinyal tanıma ile epilepsi hastalığının tespiti

This research introduces a novel approach for detecting epileptic seizures, leveraging advancements in IoT, moderate signal strength, and advanced deep learning autoencoders. The core aim is to synergize signal function performance with enhanced feature extraction capabilities of a deep learning autoencoder, thereby enabling the technology to identify optimal characteristics more efficiently and swiftly than existing traditional methods. This new method will undergo comparative analysis against various existing computational tools in the same domain. Additionally, it will be benchmarked against established studies in this field. The efficacy of this framework is underscored by its impressive 99.00% accuracy, positioning it favorably among leading research in epilepsy detection and EEG signal classification.