EEG-Based Auditory BCI for Communication in a Completely Locked-In Patient Using Volitional Frequency Band Modulation
June 30, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Deland Liu, Frigyes Samuel Racz, Zoe Lalji, Jose del R. Millan
arXiv ID
2507.00305
Category
cs.HC: Human-Computer Interaction
Cross-listed
q-bio.NC
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Patients with amyotrophic lateral sclerosis (ALS) in the completely locked-in state (CLIS) can lose all reliable motor control and are left without any means of communication. It remains unknown whether non-invasive electroencephalogram (EEG) based brain-computer interfaces (BCIs) can support volitional communication in CLIS. Here, we show that a CLIS patient was able to operate an EEG-based BCI across multiple online sessions to respond to both general knowledge and personally relevant assistive questions. The patient delivered "Yes"/"No" responses by volitionally modulating alpha and beta band power at different channels, guided by real-time auditory feedback from the BCI. The patient communicated assistive needs above chance in all sessions, achieving a perfect score in the final session. Performance on general knowledge questions varied across sessions, with two sessions showing accurate and above-chance responses, while the first and last sessions remained at chance level. The patient also showed consistent modulation patterns over time. These findings suggest that non-invasive BCIs may offer a potential pathway for restoring basic communication in CLIS.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted