Automatic, unsupervised classification of dyskinesia in patients with Parkinsons Disease
نویسنده
چکیده
One of the characteristic symptoms of patients with Parkinson Disease (PD) is a rigidity of movement. These symptoms disappear after administration of Levodopa. However, the long-term use of levodopa causes involuntary movements (dyskinesia). A proper diagnosis requires an automatic, unsupervised method for the detection and classification of levodopa induced dyskinesia. The main problem, however, is to distinguish dyskinesia from voluntary movements. The aim of this study was to train a neural network for the classification and rating of dyskinesia and to use the trained neural networks to extract parameters, which are important to distinguish between dyskinesia and normal voluntary movements. The neural network has a performance near 97% correct, which greatly improves upon previous methods (typically 75% correct).
منابع مشابه
Diabetes Increases the Incidence of Levodopa-Induced Dyskinesia in Parkinson’s Disease; A Case-Control Study
Background and Objective: Dyskinesia is a debilitating complication of Parkinsonchr('39')s disease (PD), which appears due to some known risk factors. The effect of diabetes and high plasma glucose on the manifestation of dyskinesia has been evaluated in just a few previous reports. The current study aimed to assess the mentioned correlation. Materials and Methods: In this case-control study, ...
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