Multimodal EEG-fNIRS Seizure Pattern Decoding Using Vision Transformer
Epilepsy has been analyzed through uni-modality non-invasive brain measurements such as electroencephalogram (EEG) signal, but identifying seizure patterns is more challenging due to the non-stationary nature of the brain activity and various non-brain artifacts. In this article, we leverage a visio...
Saved in:
| Main Authors: | Rafat Damseh, Abdelhadi Hireche, Parikshat Sirpal, Abdelkader Nasreddine Belkacem |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Open Journal of the Computer Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10755173/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Verbal fluency tasks and attention problems in children with ADHD: evidence from fNIRS
by: Zouji Bian, et al.
Published: (2025-07-01) -
A Wearable Functional Near-Infrared Spectroscopy (fNIRS) System for Obstructive Sleep Apnea Assessment
by: Xude Huang, et al.
Published: (2023-01-01) -
Visualization and workload with implicit fNIRS-based BCI: toward a real-time memory prosthesis with fNIRS
by: Matthew Russell, et al.
Published: (2025-05-01) -
Block-Wise Domain Adaptation for Workload Prediction from fNIRS Data
by: Jiyang Wang, et al.
Published: (2025-06-01) -
Neurocognitive dynamics and behavioral differences of symmetry and asymmetry processing in working memory: insights from fNIRS
by: Izabela Maria Sztuka, et al.
Published: (2025-02-01)