Electroencephalogram Sonification with Hybrid Intelligent System Design Based on Deep Network
The results show that the proposed CNN determines the appropriate and convergent musical scales with each EEG signal fragment and the LSTM network has a promising performance in converting the dominant frequency variations of EEG signals into note sequences. This demonstrates the good performance of the proposed sonification method.
Authors
- Ali Motie Nasrabadi (ORCID: https://orcid.org/0000-0002-3702-8547)
- Azin Movahed
- Hamidreza Jalali
- Majid Pouladian (ORCID: https://orcid.org/0000-0001-6081-6376)
Institutions
- Shahed University (IR)
- Islamic Azad University, Science and Research Branch (IR)
- Tehran University of Art (IR)
Publication Details
- Journal
- Journal of Medical Signals & Sensors
- Published
- 2025-10-01
- DOI
- https://doi.org/10.4103/jmss.jmss_85_24
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00