Detection of parkinson’s disease through speech signatures

Abstract

Parkinson’s disease is a very common neurodegenerative disorder and movement disorder. Two types of symptoms are observed in Parkinson’s disease which are motor and non-motor symptoms. Out of these, the non-motor or dopa-mine non-responsive symptoms have a major impact on the patients. Some of the non-motor symptoms are cognitive impairment, depression, REM sleep disorder, speech and swallowing difficulties, loss of smell and change in the body odor. It becomes difficult to perform basic tasks in daily routine as the symptoms aggravate. The symptoms and the rate at which the disease worsens vary from individual to individual. Patients suffering from this disease also have soft speech, impaired voice or voice box spasms. The objective of our project work is to explore this symptom and its detection. The voice signals will be captured using MATLAB. Comparison of the signals obtained with the corresponding signals of a healthy person will determine whether the individual is affected by the disease.