Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal International Journal of Informatics and Communication Technology (IJ-ICT)
Nilesh Kulkarni
Shrimati Kashibai Navale College of Engineering
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Support vector machine based alzheimer’s disease diagnosis using synchrony features Nilesh Kulkarni
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.054 KB) | DOI: 10.11591/ijict.v9i1.pp57-62

Abstract

Previous research work has highlighted that neuro-signals of Alzheimer’s disease patients are least complex and have low synchronization as compared to that of healthy and normal subjects. The changes in EEG signals of Alzheimer’s subjects start at early stage but are not clinically observed and detected. To detect these abnormalities, three synchrony measures and wavelet-based features have been computed and studied on experimental database. After computing these synchrony measures and wavelet features, it is observed that Phase Synchrony and Coherence based features are able to distinguish between Alzheimer’s disease patients and healthy subjects. Support Vector Machine classifier is used for classification giving 94% accuracy on experimental database used. Combining, these synchrony features and other such relevant features can yield a reliable system for diagnosing the Alzheimer’s disease.
Co-Authors