Diagnosis of Parkinson’s disease using deep CNN with transfer learning and data augmentation

2020 ◽  
Author(s):  
Sukhpal Kaur ◽  
Himanshu Aggarwal ◽  
Rinkle Rani
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Transfer Learning ◽  
Data Augmentation ◽  
Deep Cnn

scholarly journals Parkinson’s Disease EMG Data Augmentation and Simulation with DCGANs and Style Transfer

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2605 ◽  
Author(s):  
Rafael Anicet Zanini ◽  
Esther Luna Colombini
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Data Augmentation ◽  
Experimental Results ◽  
Generative Adversarial Networks ◽  
Style Transfer ◽  
Treatment Approaches ◽  
Adversarial Networks

This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson’s Disease (PD) electromyography (EMG) signals. The experimental results indicate that the proposed models can adapt to different frequencies and amplitudes of tremor, simulating each patient’s tremor patterns and extending them to different sets of movement protocols. Therefore, one could use these models for extending the existing patient dataset and generating tremor simulations for validating treatment approaches on different movement scenarios.

Ensemble of Deep Transfer Learning Models for Parkinson's Disease Classification

2021 ◽  
pp. 135-143
Author(s):  
Kiranbabu Rajanbabu ◽  
Iswarya Kannoth Veetil ◽  
V. Sowmya ◽  
E. A. Gopalakrishnan ◽  
K. P. Soman
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Transfer Learning ◽  
Disease Classification ◽  
Learning Models

scholarly journals Deep CNN Based Classification of the Archimedes Spiral Drawing Tests to Support Diagnostics of the Parkinson’s Disease

2020 ◽  
Vol 53 (5) ◽  
pp. 260-264
Author(s):  
Sven Nõmm ◽  
Sergei Zarembo ◽  
Kadri Medijainen ◽  
Pille Taba ◽  
Aaro Toomela
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Archimedes Spiral ◽  
Spiral Drawing ◽  
Deep Cnn
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