Non-negative matrix factorization-based time-frequency feature extraction of voice signal for Parkinson’s disease prediction
The proposed method achieved average classification accuracies of up to 92 % in vowels, and 97 % in words. There is an improvement in accuracy ranging from 10% to 40 % compared to existing methods. Further, the developed models are evaluated upon an independent dataset. Results on this separate test set show accuracies ranging from […]