DocumentCode
3565538
Title
A pattern recognition method for stage classification of Parkinson´s disease utilizing voice features
Author
Caesarendra, Wahyu ; Ariyanto, Mochammad ; Setiawan, Joga D. ; Arozi, Moh ; Chang, Cindy R.
Author_Institution
Mech. Eng. Dept., Diponegoro Univ., Semarang, Indonesia
fYear
2014
Firstpage
87
Lastpage
92
Abstract
This paper presents a pattern recognition method for multi-class classification of Parkinson´s disease based on PCA, LDA and SVM. 22 voice features which are extracted and reduced using PCA and LDA. SVM is then used during the classification step. The classification accuracy between single features and PCA and LDA features are presented and the results show that the PCA features have greater accuracy than LDA features and the single features.
Keywords
diseases; feature extraction; medical computing; pattern classification; principal component analysis; support vector machines; Parkinson´s disease stage classification; feature classification accuracy; linear discriminant analysis; pattern recognition method; principal component analysis; support vector machines; utilizing voice features; Accuracy; Feature extraction; Pattern recognition; Principal component analysis; Support vector machines; Testing; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on
Type
conf
DOI
10.1109/IECBES.2014.7047636
Filename
7047636
Link To Document