Parkinson's disease Assessment using Fuzzy Expert System and Nonlinear Dynamics
This paper proposes a new screening system for quantitative evaluation and analysis, designed for the early stage detection of Parkinson disease. This has been carried out in the view of improving the diagnosis currently established upon a basis of subjective scores. Parkinson's disease (PD) appears as a result of dopamine loss, a chemical mediator that is responsible for the body's ability to control movements. The symptoms reflect the loss of nerve cells, due to an unknown. The input parameters of the system are represented by amplitude, frequency, the spectral characteristic and trembling localization. The main symptoms include trembling of hand, arms, movement difficulties, postural instability, disturbance of coordination and equilibrium, sleep disturbance, difficulties in speaking, reducing of voice volume. The medical knowledge in PD field is characterized by imprecision, uncertainty and vagueness. The proposed system (fuzzy expert systems) is non-invasive and, easy to use by both physicians and patients at home.
parkinson's disease fuzzy expert systems nonlinear dynamics symptom assessment tremor