Identification of People with Parkinson's Suspicions through Voice Signal Processing

Parkinson is considered a disease with a very random prognosis, in addition to its origin due to a multisystemic neurodegenerative process that affects the central nervous system, which is responsible for motor control of the body and also produces chronic joint pain if the patient is not treated also suffers states of depression. This disease currently has no cure so it recommends the patient's family to provide quality of life, the age of incidence is from 40 years, according to the INCN (Instituto Nacional de Ciencias Neurológicas) indicates that there are 3,000 cases of Parkinson in Peru annually. In this research paper, it proposes the creation of an algorithm in MATLAB capable of extracting the characteristics of the voice spectrum through the voice signal processing to provide an early detection so that they can receive treatment, appease and slow down Parkinson's disease. This processing will consist of submitting the audio by the Fast Fourier Transform (FFT), identifying the signal bodies, separating by frequency periods, to finally find the average and maximum values. It was identified that in the lower frequencies are where there are major differences, in addition the test was done with patients who has Parkinson's suspicions and the same differences were obtained resulting in the frequency periods [9Hz – 13Hz], [20Hz –30Hz] and [40Hz – 54Hz]. Also note that the period of 20 Hz to 30 Hz is where if the values in this frequency are less than 3.5 in amplitude they are principles of suspicion of Parkinson's disease.

@article{Meneses-Claudio2019,
  title     = {Identification of People with Parkinson's Suspicions through Voice Signal Processing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {12},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Brian Meneses-Claudio and Witman Alvarado-Diaz and Avid Roman-Gonzalez},
  doi       = {10.14569/IJACSA.2019.0101246},
  url       = {https://doi.org/10.14569/IJACSA.2019.0101246}
}