Pathological voice assessment by recurrence quantification analysis

In this paper, the performance of quantification measures of recurrence plots is evaluated in the task of discriminating pathological voices from the healthy ones. In order to classify these signals as healthy, edema or paralysis, seven recurrence quantification measures are used: Determinism (DET), Maximum length of the diagonal structures (L_max), Entropy (ENTR), Slope of line-of-best-fit (TREND), Laminarity (LAM), Length of longest vertical line segment (V_max), and mean vertical line length or trapping time (TT). A discriminant analysis method is applied to each feature individually, using two discriminant functions: Linear and quadratic. The performance of individual classifiers are improved when combining the measures two by two. Results show that the method employed can be used as a highly reliable method for pathological voice assessment.