Early detection of Alzheimer’s disease from EEG signals using Hjorth parameters
Objective
The primary objective of this research study is to develop an accurate and reliable method for the early detection of Alzheimer's disease through the analysis of electroencephalogram (EEG) signals, utilizing Hjorth parameters as key indicators.
Abstract
This research study aims to revolutionize the early detection of Alzheimer's disease by harnessing the power of electroencephalogram (EEG) signals and leveraging Hjorth parameters as pivotal diagnostic indicators. Alzheimer's, a progressive neurodegenerative disorder, poses a significant global health challenge, and early diagnosis remains paramount for effective intervention. Through meticulous analysis of EEG data, this study seeks to unearth subtle yet distinctive patterns that precede the clinical manifestation of Alzheimer's. By focusing on Hjorth parameters, which offer insights into signal complexity, activity, and mobility, this research strives to provide a robust and precise method for identifying the disease in its incipient stages. The potential impact of this work is profound, offering not only earlier intervention opportunities but also the possibility of monitoring disease progression, ultimately enhancing the quality of life for individuals at risk of or already afflicted by Alzheimer's disease.
Keywords: signal Processing, Hjorth parameters, Alzheimer’s disease.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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