Online ISSN: 2515-8260

Keywords : Parkinson’s disease


ASSESSMENTS OF MOTOR AND NON-MOTOR DISORDERS (ORTHOSTATIC HYPOTENSION) OF PATIENTS WITH PARKINSON’S DISEASE

Gaffarova Pаrvina Abdurafikovna; Khakimova Sohiba Ziyadulayevna

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 1, Pages 2178-2182

The patients with Parkinson’s disease have been studied for motor disorders in early, mid, and advanced stages. We have used The Hoehn and Yahr scale and UPDRS (Unified Parkinson Disease Rating Scale) for that. Orthostatic test was used for orthostatic hypotension. As a result, it has been detected that as the disease progresses, motor disorder of the limbs progresses as well. However, orthostatic hypotension was recorded much more often in patients with advanced and late stages of the disease

Parkinson's Disease Detection using Convolutional Neural Networks

Manisha Jindal; Yogesh Tripathi

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 6, Pages 1298-1307

These days, a significant research exertion in social insurance biometrics is finding exact biomarkers that permit creating clinical choice help instruments. These instruments aid with the diagnosis and treatment of diseases such as Parkinson's disease. In this article, a convolutionary neural network (CNN) for the PD identification from drawing production is broken. This CNN comprises two parts: extraction and arranging (completely linked layers). CNN involves two pieces. CNN refers to the increase in frequency volume from 0 Hz to 25 Hz by the Fast Fourier Module. Throughout the modeling cycle the separating capacity of various headings tested achieved the greatest outcomes for both X & Y rollers. This research has been conducted using open database: a digital image tablet dataset from Parkinson Spiral Drawings. This study produced 96.5 percent of precision, 97.7 percent of F1 and 99.2 percent of region. There were the strongest results.