International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI Oriented System to Identify Type of Epilepsy Seizure Using EEG Wave

Author(s) Dr.K.Rama, Karlakunta Vamshi, Mikkilineni Pradeep, Chatla Vinay Kumar
Country India
Abstract For practical purposes, over the past three decades, several methods have been devised to mitigate various anomalies within corrupted EEG data. Nonetheless, there is still no universally acclaimed technique, rendering the field of study both intriguing and challenging. This research delves comprehensively into the identification and elimination of artifacts originating from ocular, muscular, and cardiac sources, offering a detailed analysis of their respective advantages and drawbacks. Furthermore, this investigation encompasses the methodologies employed for comparing real EEG data with simulated counterparts, serving to authenticate their efficacy. The primary focus of this work is twofold: firstly, to establish standardized criteria for the validation of recorded EEG signals in forthcoming studies, and secondly, to amalgamate diverse techniques through multiple processing stages, thereby facilitating the effective eradication of interference stemming from artifacts.
Keywords Resolution, EEG, Artifacts, techniques, Validate
Field Engineering
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-11-09
Cite This AI Oriented System to Identify Type of Epilepsy Seizure Using EEG Wave - Dr.K.Rama, Karlakunta Vamshi, Mikkilineni Pradeep, Chatla Vinay Kumar - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.8594
DOI https://doi.org/10.36948/ijfmr.2023.v05i06.8594
Short DOI https://doi.org/gs38gv
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