Fig. 1.

Flowchart of our method. First, we downloaded data from the Synapse portal. These audio signals were divided into frames, and features were extracted utilizing MFCC feature extraction. The most predictive MFCC features were selected utilizing L1-based feature selection, and these selected features were classified into Parkinson's and control groups using an RBF-Kernel SVM classifier to output a diagnosis. MFCC, mel-frequency cepstral coefficient; RBF, radial basis function; SVM, support vector machine.