Moving Towards Measuring Spatial Hearing Using Consumer-grade Headband EEG
Why this work is in the frame
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Bibliographic record
Abstract
Binaural hearing allows individuals to perceive the spatial location of sound sources, a process that engages multiple brain regions and allows for selective auditory attention while filtering out background noise and interference. Understanding the neural mechanisms underlying binaural processing requires a reliable method for capturing brain activity in response to binaural stimuli. While clinical-grade Electroencephalography (EEG) has proven a powerful tool for this task, it is only available in clinical labs and involves complex setup. This study investigates the feasibility of moving towards consumer-grade wearable biosensors for investigation of binaural hearing. Using the MUSE S headband as a representative of this family of devices, neural responses to binaural auditory stimuli are measured and compared against those of a clinical-grade EEG system. Participants completed a horizontal sound localization test while EEG data were recorded using both devices. Signal processing methods were applied to the resulting signals to evaluate the power of key frequency bands—specifically delta and alpha bands. Results demonstrate that, while the MUSE S reliably captures delta and alpha activity similar to a clinical EEG in its covered regions, limitations exist due to its sparse electrode placement, particularly in capturing spatial hearing components outside frontal and temporal regions. The findings highlight the potential of wearable sensors for accessible auditory testing while emphasizing the need for additional electrodes to enhance binaural hearing assessments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it