Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques publicado no periódico Pattern Recognition Letter (Elsevier), JCR 1.95
Parabéns aos colaboradores do LAPISCO pelo trabalho intitulado “Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques” publicado no periódico Pattern Recognition Letter (Elsevier), JCR 1.95. . Abstract: This study investigates the processing of voice signals for detecting Parkinson’s disease. This disease is one of the neurological disorders that affect people in the world most. The approach evaluates the use of eighteen feature extraction techniques and four machine learning methods to classify data obtained from sustained phonation and speech tasks. Phonation relates to the vowel /a/ voicing task and speech to the pronunciation of a short sentence in Lithuanian language. TheRead More →