A hybrid two-stage SqueezeNet and support vector machine system for Parkinson’s disease detection based on handwritten spiral patterns

• Published in: International journal of applied mathematics and computer science Vol. 31; no. 4; pp. 549 - 561
• Main Authors: Bernardo, Lucas Salvador, Damaševičius, Robertas, De Albuquerque, Victor Hugo C., Maskeliūnas, Rytis
• Format: Journal Article
• Language: English
• Published: Zielona Góra Sciendo 01.12.2021; De Gruyter Poland
• Subjects: Artificial neural networks; Classifiers; convolutional neural network; deep learning; Digital imaging; Feature extraction; Handwriting; Machine learning; Neurological diseases; Parkinson's disease; spirography; Support vector machines; Training

Parkinson’s disease (PD) is the second most common neurological disorder in the world. Nowadays, it is estimated that it affects from 2% to 3% of the global population over 65 years old. In clinical environments, a spiral drawing task is performed to help to obtain the disease’s diagnosis. The spira...