A Critical Study towards the Detection of Parkinson’s Disease using ML Technologies

  • Vivek Chetia, Abdul Taher Khan, Rahish Gogoi, David Kapsian Khual, Purnendu Bikash, Sajal Saha
Keywords: Machine Learning, CNN, Models, Convolution, ReLU, Pooling, Augmentation

Abstract

In this paper, we have implemented a mobile application to detect Early Parkinson’s Disease using the Convolutional Neural Network (CNN) model. Using spiral and wave images, with the help of Transfer learning and Image Augmentation, we have trained our model to detect Parkinson's Disease. To generate the result, the mobile application uses the device's camera and storage to access images of spiral and wave drawn by the user. Final result is generated by comparing the result of spiral and wave images. We have achieved accuracy of  95%  on Spiral images and 92% on Wave images

Published
2022-01-29
How to Cite
Purnendu Bikash, Sajal Saha, V. C. A. T. K. R. G. D. K. K. (2022). A Critical Study towards the Detection of Parkinson’s Disease using ML Technologies. Design Engineering, (1), 988-996. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/8961
Issue
Vol 2022: Issue 01
Section
Articles