EEG-Based Classification of Parkinson’s Disease With Freezing of Gait Using Midfrontal Beta Oscillations
These findings support the potential of midfrontal beta oscillations, particularly in combination with LSTM temporal modeling, a promising EEG-based biomarker for distinguishing PDFOG+ from PDFOG-. This work contributes to the development of more effective diagnostic tools and treatment strategies for PD-related gait impairments.
Authors
- Joseph Nuamah (ORCID: https://orcid.org/0000-0001-7172-0716)
- Shotabdi Roy (ORCID: https://orcid.org/0000-0003-1178-400X)
- Richa Barsainya
- Maximilian Scherer (ORCID: https://orcid.org/0000-0002-5280-2828)
- Taylor J. Bosch (ORCID: https://orcid.org/0000-0002-6633-7525)
- Arun Pratap Singh (ORCID: https://orcid.org/0000-0003-4273-542X)
- Thomas Koeglsperger (ORCID: https://orcid.org/0000-0001-6101-0323)
- KC Santosh (ORCID: https://orcid.org/0000-0003-4176-0236)
Institutions
- Oklahoma State University (US)
- University of South Dakota (US)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of Integrative Neuroscience
- Published
- 2025-06-20
- DOI
- https://doi.org/10.31083/jin39023
- Citations
- 1
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- Loyola University Chicago Stritch School of Medicine