Graph visualization of correlation matrix for the vocal measurements, with the color map ranging from blue (for negative correlation coefficient) to red (for positive correlation coefficient).

<p>Graph visualization of correlation matrix for the vocal measurements, with the color map ranging from blue (for negative correlation coefficient) to red (for positive correlation coefficient).</p

Figure 6

<p>Scatter plots of the vocal patterns associated with the healthy controls (CO) and patients with Parkinson’s disease (PD) in the two-dimensional feature spaces of (<b>A</b>) MDVP: F0 and MDVP: Jitter (%), (<b>B</b>) MDVP: F0 and detrended fluctuation analysis (DFA), (<b>C</b>) MDVP: F0 and Spread2, (<b>D</b>) MDVP: Jitter (%) and DFA, (<b>E</b>) MDVP: Jitter (%) and Spread2, and (<b>F</b>) DFA and Spread2, respectively.</p

Statistics of the vocal measurements selected by the sequential forward selection (SFS) method.

<p>CO: healthy controls; PD: Parkinson’s disease; DFA: detrended fractal analysis.</p

Bivariate distributions of vocal patterns in the kernel principal component analysis (KPCA) mapping feature plane.

<p>Vocal pattern distributions for the healthy controls (CO) and patients with Parkinson’s disease (PD) are displayed with the cold color map (blue for the highest density) and hot color map (red for the highest density), respectively.</p

Details of subject information on the records misclassified by the maximum <i>a posteriori</i> (MAP) and support vector machine (SVM) classifiers.

<p>M: male; F: female; CO: healthy controls; PD: Parkinson’s disease; H&Y stage: Hoehn and Yahr stage; N/A: not applicable for healthy subjects.</p

Figure 5

<p>Diagnostic performance of the classifiers: (<b>A</b>) receiver operating characteristic (ROC) curves produced by the maximum <i>a posteriori</i> (MAP) classifier, support vector machine (SVM), and Fisher’s linear discriminant analysis (FLDA); (<b>B</b>) results of classification accuracy, sensitivity, specificity, and area under receiver operating characteristic (ROC) curve obtained by the three classifiers.</p