Author(s)

Badra Khellat Kihel, Mohamed Benyettou

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This work deals the application of the artificial immune system to discriminate between healthy and people with Parkinson’s disease (PWP). As the symptoms of Parkinson’s disease (PD) occur gradually and mostly targeting the elderly people for whom physical visits to the clinic are inconvenient and costly, telemonitoring of the disease using measurements of dysphonia (vocal features) has a vital role in its early diagnosis. Taking inspiration from natural immune systems, we try to grab useful properties such as automatic recognition, memorization and adaptation. The developed algorithms have as a base the algorithm of training bio inspired CLONCLAS. The results obtained are satisfactory and show a great reliability of the approach.

Parkinson’s Disease, Dysphonia Measures, Speech Analysis, Immune System, Clonal Selection Algorithm

B. Kihel and M. Benyettou, "Parkinson’s Disease Recognition Using Artificial Immune System," Journal of Software Engineering and Applications, Vol. 4 No. 7, 2011, pp. 391-395. doi: 10.4236/jsea.2011.47045.