Work place: Department of Computer Science & Engineering, B.L.D.E.A’s V.P. Dr. P.G. Halakatti College of Engineering and Technology, Vijayapur-586103, Karnataka, Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India
E-mail: anilkannur1978@gmail.com
Website:
Research Interests: Digital Forensics, Image Processing
Biography
Dr. Anil Kannur has 21 years of experience in teaching and 9 years in research. He has published many research articles in journals and conferences of repute. His areas of interest include Digital Forensics, BCI and Image Processing.
By Anand Ghuli Anil Kannur Abhishek Mali Aishwarya Mangasuli
DOI: https://doi.org/10.5815/ijisa.2024.02.04, Pub. Date: 8 Apr. 2024
Epilepsy is considered one of the primary neurological disorders, and its treatment requires abundant technological assistance. General Anaesthesia induces distinct patterns in brain activity, with the most common being a gradual increase in low-frequency signals as the level of Anaesthesia deepens. In this instance, a method of validating epileptic seizures and Anaesthesia through the utilization of electroencephalogram (EEG) data, acquired non-invasively, is introduced. Epileptic seizures and detection of the presence of Anaesthesia approaches make use of discrete Laplace Transformation (LT), Discrete Cosine Transformation (DCT), and Fast Fourier Transform (FFT). Here, it is discussed how power spectral analysis (PSA) helps study EEG characteristics in detecting epileptic behavior and the presence of Anaesthesia. A dataset of EEG (Epileptic and Anaesthesia), which is available publicly [1,2], has been used in the propounded technique using FIR filters and LT, DCT, and FFT are used to store and process 16 channel data. Power Spectrum Density (PSD) and its average were contrasted against a specific spectrum and frequency range of a typical EEG signal to obtain the results. This work uses a technique to determine whether the patient being studied is epileptic and awake or anesthetized.
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