Tracking Human Daily Cognitive Activity from EEG and Biometric Data
2.40T1 sourcearXiv cs.HC
Source record
Published by arXiv cs.HC (T1 source). The original is at https://arxiv.org/abs/2610.02971.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryA pilot study (N=3) proposes a multimodal framework for tracking daily cognitive activity using EEG, wearable physiological signals, behavioral context, and self-reports. Over 280 annotated intervals spanning two weeks, it reports a mid-day motivation dip at 13:00, highest flow rates during work (51%) and IADLs (50%), and a linear regression predicting motivation (R²=0.76).
Why it mattersVery small sample (N=3) limits generalizability. Worth noting as an early attempt to combine EEG with physiological and behavioral signals outside the lab.
Cited by
No citations on record.
