Detection of Parkinson's Disease through Acoustic Parameters

Parkinson’s disease is a neurological disorder. It is the second most common disease after Alzheimer’s. Incidence rates for this disease are increasing rapidly with increasing life expectancy. The search for measures to diagnose the disease and monitor symptoms is an important step, despite the fact that it presents a number of challenges. Among the symptoms related to this disease is the disturbances of the voice which particularly occur in a remarkable way called hypokinetic dysarthria which is presented by the poverty of the gesture in all the characteristics of the speech (phonatory, prosodic, articulatory and rhythm). Our goal is to do a study based on voice analysis at the level of the glottis to examine some early parameters measured using the LF model and clinical manifestations to help diagnosis of the disease.

@article{Daly2018,
  title     = {Detection of Parkinson's Disease through Acoustic Parameters},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {7},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Imen Daly and Zied Hajaiej and Ali Gharsallah},
  doi       = {10.14569/IJACSA.2018.090742},
  url       = {https://doi.org/10.14569/IJACSA.2018.090742}
}