Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms.
Automated detection of emotional states through brain-computer interfaces (BCIs) offers significant potential for enhancing user experiences and personalizing services across domains such as mental health, adaptive learning and interactive entertainment. Within this advancing field, the aim of this...
Saved in:
| Main Authors: | Ayşenur Eser, Sinem Burcu Erdoğan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0325850 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Cortical Spatial Responses and Decoding of Emotion Imagery Toward a Novel fNIRS-Based Affective BCI
by: Xiaopeng Si, et al.
Published: (2025-01-01) -
Simultaneous EEG and fNIRS recordings for semantic decoding of imagined animals and tools
by: Milan Rybář, et al.
Published: (2025-04-01) -
Multimodal EEG-fNIRS Seizure Pattern Decoding Using Vision Transformer
by: Rafat Damseh, et al.
Published: (2024-01-01) -
iTBS on RDLPFC improves performance of motor imagery: a brain-computer interface study combining EEG and fNIRS
by: Jialin Chen, et al.
Published: (2025-07-01) -
Gustatory-Visual Interaction in Human Brain Cortex: fNIRS Study
by: Karolina Jezierska, et al.
Published: (2025-01-01)