Please use this identifier to cite or link to this item:
Title: Classification of different type of seizure using machine learning approach
Authors: Low, Li Yian
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: The following Final Year Project gives an overview of the work done by the student for Classification of different types of seizures using machine learning approach, with different methods avaliable. The report consists of 6 chapters – Chapter 1: Objectives of the project and introduction of EEG backgrounds, Chapter 2: Pre-processing and seizure segments, Chapter 3: Feature Extraction methods and results, Chapter 4: Feature Selection and results, Chapter 5: Classification and final results, Chapter 6: Conclusion on the results, future work and reflection.
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Report (Revised) U1622398J.pdf
  Restricted Access
2.65 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 13, 2024


Updated on Jun 13, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.