7th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 2011)
Parkinson's disease (PD) is a neurological illness characterized by progressive loss of dopaminergic neurons, primarily in the substantia nigra pars compacta. changes in speech associated with hypokinetic dysarthria are a common manifestation in patients with idiopathic PD. the aim of this study is to investigate the feasibility of automated acoustic measures for the identification of voice and speech disorders in PD. the speech data were collected from 46 czech native speakers, 24 with early PD before receiving pharmacotherapy treatment. We have applied several traditional and non-standard measurements in combination with statistical decision-making strategy to assess the extent of vocal impairment of recruited speakers. subsequently, we have applied support vector machine to find the best combination of measurements to differentiate PD from healthy subjects. this method leads to overall classification performance of 85%. admittedly, we have found relationships between measures of phonation and articulation and bradykinesia and rigidity in PD. in conclusion, the acoustic analysis can ease the clinical assessment of voice and speech disorders, and serve as measures of clinical progression as well as in the monitoring of treatment effects.
Index Terms. parkinson's disease, speech disorders, hypokinetic dysarthria, acoustic analysis, biomedical application
Full Paper (reprinted with permission from Firenze University Press)
Bibliographic reference. Rusz, Jan / Cmejla, R. / Ruzickova, H. / Klempir, J. / Majerova, V. / Picmausova, J. / Roth, J. / Ruzicka, E. (2011): "Acoustic analysis of voice and speech characteristics in early untreated Parkinson's disease", In MAVEBA-2011, 181-184.