EEG-Based Focus Estimation Using Neurable’s Enten Headphones and Analytics Platform

We introduce Neurable’s research on focus using our recently developed Enten EEG headphones. First we quantify Enten’s performance on standard EEG protocols, including eyes-closed alpha rhythms, auditory evoked response and the P300 event-related potential paradigm. We show that Enten’s performance is on-par with established industry-standard hardware. We then introduce a series of experimental tasks designed to mimic how focus might be maintained or disrupted in a real-world office setting. We show that (A) these tasks induce behavioral changes that reflect underlying changes in focus levels and (B) our proprietary algorithm detects these changes across a large number of sessions without needing to adjust the model per participant or recording session. Through manipulation of our experimental protocol, we show that our algorithm is not dependent on gross EMG artifacts and it is driven by changes in EEG. Finally, we evaluated the model’s performance on the same subject across several days, and show that performance remained consistent over time. Our model correctly captured 80% ± 4.1% of distractions present in our experiments with statistical significance. This indicates that our model generalizes across subjects, time points, and conditions. Our findings are based on EEG data collected from 132 participants across 337 sessions and 45 different experiments. ### Competing Interest Statement The authors have declared no competing interest.