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Original Article

Multimodal Deep Learning Approach for Parkinson’s Disease Recognition

  • Paper ID 382
  • Volume 6, Issue 3
  • Pages 283-289
  • Published Online: May-June 2026
  • 18 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Dr.Sayyad Rasheeduddin1
  • K. Sai Krishna2
  • B. Ganesh3
  • S. Arun4

1 Associate Professor, Department of CSE (AI & ML), CMR Engineering College, Hyderabad, Telangana, India. 2 3 4 Research Scholar, Department of CSE (AI & ML), CMR Engineering College, Hyderabad, Telangana, India.

Article Information

Published Online
May-June 2026
Pages
283-289
Article Type
Original Article
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References

1. A. H. Behroozi, A. Nosratighods, and M. G. Shayesteh, “Diagnosis of PD Using Deep Neural Network Classifier,” Journal of Biomedical Informatics, vol. 98, pp. 103-112, 2021.
2. S. Prashanth, R. Dutta Roy, P. Mandal, and S. Ghosh, “Predicting Seriousness of PD Using Deep Learning,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 8, pp. 1448-1456, 2018.
3. J. W. Fisher, M. Z. Khan, and A. G. Jacob, “Deep Learning-Aided Parkinson’s Disease Diagnosis from Handwritten Dynamics,” Expert Systems along with Applications, vol. 176, pp. 113-121, 2022.
4. M. E. Ashtari, R. Maleki, and A. J. Tarokh, “Refining Diagnosis of Parkinson’s Disease with Deep Learning-Based Interpretation of Dopamine Transporter Imaging, 2021.
5. J. Q. Zhangu, K. H. Wong, and C. Y. Lau, “End-to-End Parkinson Disease Diagnosis Using Brain MRI Images by 3D-CNN,” Neurocomputing, vol. 403, pp. 49-90, 2020.
6. B. Wang, Y. Liu, and X. Wang, “Analysis and Identification of Parkinson’s Disease Based on fMRI,” International Journal of Imaging Systems and Technology, vol. 31, no. 3, pp. 521-532, 2021.
7. H. T. Nguyen, P. C. Le, and T. H. Tran, “Prediction of Parkinson’s Disease Tumor On Using a Radial Function Neural Network Based on Particle Swarm Optimization,” Applied Soft Computing, vol. 100, pp. 107-129, 2022.
8. UCI Machine Learning Repository, “Parkinson’s Telemonitoring Voice Data Set,” University of California, Irvine, 2009. [Online]. Available: https://archive.ics.uci.edu/ml/datasets/Parkinsons
9. Physio Network, “Gait in Parkinson’s Disease Database,” MIT Laboratory for Computational Physiology, 2019. [Online]. Available: https://physioonet.org/content/gaitpdb/
10. World Health Organization (WHO), “Neurological Disorders: Public Health Challenges,” WHO Reports, 2020.[Online]Available: https://www.who.int/publications-detail/neurological-disorders
11. P. Martinez Martin, W. A. Chaudhuri, and L. Rodriguez-Blazquez, “The Impact of Parkinson’s Disease Health Costs: A Global Perspective,” Journal of Parkinson’s Disease, vol. 9, no. 3, pp. 530-542, 2021.
12. K. P. Bhatt, M. A. Grosman, and J. F. Bender, “Machine Learning Based Parkinson’s Disease Detection Using Voice Data: A Review,” Biomedical Signal Processing and Control, vol. 68, pp. 102-120, 2022. Image and Vision Computing, vol. 15(8), pp. 646–654, (1999).
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