Detection of Parkinson’s Disease through Smell Signatures

Parkinson's Disease is a neurodegenerative and intensifying disorder. The symptoms of this disease are classified into two types - motor and non-motor symptoms. Some of the motor symptoms are instability in posture, bradykinesia, tremor, etc while on the other hand, the non-motor symptoms are changes in body odor, sleep disorders, difficulty in swallowing and depression. The intensity of these symptoms differs from person to person. Amongst these two types of symptoms, non-motor symptoms are identifiable at an early stage. Hence detection of these symptoms helps in recognizing whether a person has Parkinson's Disease at an early stage. Patients diagnosed with Parkinson's Disease give out a distinguishable musky smell. The paper describes a non-intrusive and definite method for detecting Parkinson's disease through an individual's smell signatures. VOC sensors which determine the components in sweat were used to achieve this objective. The sensors were interfaced with Arduino UNO, which in turn gave the values of the different components of sweat in the Arduino programming software. The values of the various components of sweat obtained from people with Parkinson's Disease and healthy individuals is compared. This comparison is used to determine whether that person is suffering from the disease. The proposed system can be utilized by clinicians in their annual health check-ups without the usage of exorbitant diagnostic tools.