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Parkinsonís disease Diagnosis using Mel-frequency Cepstral Coefficients and Vector Quantization
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 14 - Number 3 |
| Year of Publication: 2011 |
| Authors: Tripti Kapoor, R.K. Sharma |
10.5120/1821-2393
|
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
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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