Parkinson's disease is a neurodegenerative disease that negatively affects millions of lives. The diagnosis of Parkinson's disease is usually based on determining the decrease in dopaminergic neurons using some clinical tests, such as radionuclide positron emission tomography or single photon emission computed tomography. Nevertheless, there are various studies in the literature to diagnose the disease remotely. Although there is no available treatment method yet that prevents or cures Parkinson's disease, partial treatments are applied for various symptoms of the disease. Motor and non-motor symptoms include tremor, stiffness, postural instability, depression, and anxiety. Along with these various symptoms, Parkinson's patients were found to exhibit gait variability. In this study, the gait signals of Parkinson's disease patients were examined and the relationship between severity of Parkinson's disease and gait variability was revealed. Gait signals are one dimensional signals and they were visualized with fuzzy recurrence plot method. Time series signals were converted to images, which contains textural information, by the aid of fuzzy recurrence plot. In the visualized data, autocorrelation, contrast, correlation, cluster priority, cluster shadow, dissimilarity, energy, entropy, homogeneity and maximum probability parameters were computed by using gray level co-occurrence matrix. The relationship between the computed parameters and, Hoehn&Yahr, UPDRS and MDS-UPDRS, which are rating scales to assess severity of Parkinson’s disease, were evaluated. According to the obtained results autocorrelation, cluster priority, energy, entropy, and maximum probability parameters were found to be correlated with all rating scales. Although entropy shows a positive correlation, others have a negative correlation. Correlation and cluster shadow parameters were found to be not related to the rating scales. The fact that the Hoehn&Yahr rating scale has higher results, reveals that it is more discriminative. The innovative part of this study is demonstration of the relationship between gait variability and the severity of Parkinson's disease with computational methods.
Publication Date : August 31, 2020
|APA||Cantürk, İ . (2020). Parkinson Hastalığının Derecesi ile Yürüyüş Değişkenliği Arasındaki İlişkinin Bulanık Tekrarlılık Grafiğine Göre Araştırılması . Avrupa Bilim ve Teknoloji Dergisi , (19) , 410-419 . DOI: 10.31590/ejosat.699099|