Abstract
For a proper diagnosis, Parkinson's disease (PD) requires frequent visits to the doctor for physical tests, causing a huge burden on the patient. As PD impairs the handwriting ability, the handwriting pattern can be used as an indicator for PD diagnosis. More specifically, the Static Spiral Test (SST) and the Dynamic Spiral Test (DST), that consists in retracing spirals using digital pen. Such exam can be self-conducted by the patient, and thus it would be convenient and non-time-consuming for both the patient and the medical staff. In this project, we designed and implemented a system that automatically self-aid-diagnoses PD using SST and DST on digital tablets. The system includes two main components, image processing techniques to pre-process and extract the appropriate visual features and machine learning techniques to recognize PD automatically. The conducted experiment showed that the semi-local Edge Histogram Descriptor extracted from DST drawing, and conveyed to a Gaussian Kernel Support Vector Machine outperforms the other considered systems with an accuracy, specificity and sensitivity around 90%.
Highlights
Parkinson's disease (PD) is a disorder that degenerates neurons which yields to failure of motor function because of smaller ratio of dopamine that is produced in brain [1], it affects the patient motor abilities such as speaking, writing, and walking
Since PD is a type of movement disorder that impairs handwriting ability, we propose a system that will detect PD using the handwriting pattern
The results showed that the highest accuracy rate is obtained when using spiral test and Support Vector Machine (SVM) classifier [7]
Summary
Parkinson's disease (PD) is a disorder that degenerates neurons which yields to failure of motor function because of smaller ratio of dopamine that is produced in brain [1], it affects the patient motor abilities such as speaking, writing, and walking. Its symptoms often appear gradually without being noticed by the patient. They are classified into those affecting movement (motor symptoms) and those that do not (non-motor symptoms). One of the primary motor symptoms is the tremor which is an unintentional, rhythmic, slow muscle movement [3]. It occurs when the person is motionless and begins either in one hand, one foot, or one leg [2]
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