Jan. 31, 2024, 4:46 p.m. | Gianpaolo Palo, Luigi Fiorillo, Giuliana Monachino, Michal Bechny, Mark Melnykowycz, Athina Tzovara, Valentina Agostini, Francesca Dalia Faraci

cs.LG updates on arXiv.org arxiv.org

Study Objectives: Polysomnography (PSG) currently serves as the benchmark for
evaluating sleep disorders. Its discomfort, impracticality for home-use, and
introduction of bias in sleep quality assessment necessitate the exploration of
less invasive, cost-effective, and portable alternatives. One promising
contender is the in-ear-EEG sensor, which offers advantages in terms of
comfort, fixed electrode positions, resistance to electromagnetic interference,
and user-friendliness. This study aims to establish a methodology to assess the
similarity between the in-ear-EEG signal and standard PSG.


Methods: We assess …

analysis arxiv assessment benchmark bias comparison cost data eeg eess.sp exploration home introduction quality sensor sleep standard study

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US