New Cues in Low-Frequency of Speech for Automatic Detection of Parkinson's Disease

In this paper, the analysis of low-frequency zone of the speech signals from the five Spanish vowels, by means of the Teager energy operator (TEO) and the modified group delay functions (MGDF) is proposed for the automatic detection of Parkinson’s disease. According to our findings, different implementations of the TEO are suitable for tackling the problem of the automatic detection of Parkinson’s disease. Additionally, the application of MGDF for improving the resolution of the speech spectrum in the low frequency zone is able for enhancing differences exhibited between the first two formants from speech of people with Parkinson’s disease and healthy controls. The best results are obtained for vowel /e/, where accuracy rates of up to 92% are achieved. This is an interesting result specially if it is considered that there are muscles that are involved in the production of the vowel /e/ but not in other vowels.