Parkinson’s disease diagnosis using convolutional neural networks and figure-copying tasks

Alissa, Mohamad; Lones, Michael A.; Cosgrove, Jeremy; Alty, Jane E.; Jamieson, Stuart; Smith, Stephen L.; Vallejo, Marta

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that causes abnormal movements and an array of other symptoms. An accurate PD diagnosis can be a challenging task as the signs and symptoms, particularly at an early stage, can be similar to other medical conditions or the physiological changes of normal ageing. This work aims to contribute to the PD diagnosis process by using a convolutional neural network, a type of deep neural network architecture, to differentiate between healthy controls and PD patients. Our approach focuses on discovering deviations in patient’s movements with the use of drawing tasks. In addition, this work explores which of two drawing tasks, wire cube or spiral pentagon, are more effective in the discrimination process. With \(93.5\%\) accuracy, our convolutional classifier, trained with images of the pentagon drawing task and augmentation techniques, can be used as an objective method to discriminate PD from healthy controls. Our compact model has the potential to be developed into an offline real-time automated single-task diagnostic tool, which can be easily deployed within a clinical setting.

Citation

Alissa, M., Lones, M. A., Cosgrove, J., Alty, J. E., Jamieson, S., Smith, S. L., & Vallejo, M. (2022). Parkinson’s disease diagnosis using convolutional neural networks and figure-copying tasks. Neural Computing and Applications, 34, 1433-1453. https://doi.org/10.1007/s00521-021-06469-7

• Journal Article Type: Article
• Acceptance Date: Aug 26, 2021
• Online Publication Date: Sep 8, 2021
• Publication Date: 2022-01
• Deposit Date: Sep 23, 2021
• Publicly Available Date: Sep 23, 2021
• Journal: Neural Computing and Applications
• Print ISSN: 0941-0643
• Electronic ISSN: 1433-3058
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 34
• Pages: 1433-1453
• DOI: https://doi.org/10.1007/s00521-021-06469-7
• Keywords: Convolutional neural networks, Parkinson’s disease, Drawing tasks, Deep learning classifier, Diagnosis
• Public URL: http://researchrepository.napier.ac.uk/Output/2804730