Studying on signals of EMG and data mining application
2008
0 views
0 downloads
Advisor: Prof. Dr. Etem Köklükaya
Abstract (EN)
In the current work we propose a methodology for the automated creation of data analyzing with using data mining techniques and applied in Myopathy and Neuropathy beat classification.A Java based machine learning pocket WEKA (Waikato Environment for Knowledge Analysis) data mining platform which is developed by University of Waikato in New Zealand, used for data analyzingIn the current work we obtained high truth (% 95) for disease identification.Key Words: Electromyography, Myopathy, Neuropathy, Data mining
Author
Dr. Evren Arslan
Institution
How to Cite
Evren Arslan (Master Thesis). Studying on signals of EMG and data mining application, 2008, Sakarya University, Elektrik ve Elektronik Mühendisliği Bölümü.
License
Tüm Hakları Saklıdır
This work is shared under the specified license terms.
More theses from Sakarya University
- Computational investigation of battery materials using density functional theory(2023)
- Haci Ahmed b. Seyyid al-Bigavî and Tarjama al-Awārif al-maārif (sections of 22-43)(2024)
- Synthesis of carbazol substituted 3,4-dihydropyrimidine-2(1h)-thione deri̇vati̇ves(2024)
- Classification of recyclable wastes with deep learning models: A comparison on the effect of dataset size(2024)
- Hermeneutical analysis of sacrifice, sacred violence and scapegoat motifs in Turkish Mythology(2024)
- Novel thio-chalcone substituted metallophthalocyanines: synthesis, characterization and redox behaviour(2018)