Research Article
Parkinsonís disease Diagnosis using Mel-frequency Cepstral Coefficients and Vector Quantization
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 14 - Issue 3 |
| Published: January 2011 |
| Authors: Tripti Kapoor, R.K. Sharma |
10.5120/1821-2393
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Tripti Kapoor, R.K. Sharma . Parkinsonís disease Diagnosis using Mel-frequency Cepstral Coefficients and Vector Quantization. International Journal of Computer Applications. 14, 3 (January 2011), 43-46. DOI=10.5120/1821-2393
@article{ 10.5120/1821-2393,
author = { Tripti Kapoor,R.K. Sharma },
title = { Parkinsonís disease Diagnosis using Mel-frequency Cepstral Coefficients and Vector Quantization },
journal = { International Journal of Computer Applications },
year = { 2011 },
volume = { 14 },
number = { 3 },
pages = { 43-46 },
doi = { 10.5120/1821-2393 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2011
%A Tripti Kapoor
%A R.K. Sharma
%T Parkinsonís disease Diagnosis using Mel-frequency Cepstral Coefficients and Vector Quantization%T
%J International Journal of Computer Applications
%V 14
%N 3
%P 43-46
%R 10.5120/1821-2393
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper investigates the adaptation of MFCCs to the diagnosis of Parkinson’s disease (PD). The aim of this study is to provide a novel method, suitable for keeping track of the evolution of the patient’s pathology: easy-to-use, fast, non-invasive for the patient, and affordable for the clinicians. This method will be complementary to the existing ones - the perceptual judgment and the usual objective measurement (jitter, airflows...) which remain time and human resource consuming. The system designed for this particular task relies on the Mel-Frequency Cepstral coefficients (MFCC) for feature extraction and Vector Quantization (VQ) for feature analysis which is the state-of-the-art for speaker recognition.
References
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