activity
20232026
most citedComparison analysis between standard polysomnographic data and in-ear-EEG signals: A preliminary study

6 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026

Detecting Drunk Driving Using Off-the-Shelf Smartwatches

Robin Deuber, Lanlan Yang, Michal Bechny +9

Alcohol-impaired driving remains a major yet preventable cause of road traffic injury and death, with many drivers underestimating their level of intoxication. Compared to in-vehic…

cs.LG2025

SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models

Alvise Dei Rossi, Matteo Metaldi, Michal Bechny +7

Despite advances in deep learning for automatic sleep staging, clinical adoption remains limited due to challenges in fair model evaluation, generalization across diverse datasets,…

stat.AP2025

Unveiling Sleep Dysregulation in Chronic Fatigue Syndrome with and without Fibromyalgia Through Bayesian Networks

Michal Bechny, Marco Scutari, Julia van der Meer +4

Chronic Fatigue Syndrome (CFS) and Fibromyalgia (FM) often co-occur as medically unexplained conditions linked to disrupted physiological regulation, including altered sleep. Build…

eess.SP2024★ 6 cited

Comparison analysis between standard polysomnographic data and in-ear-EEG signals: A preliminary study

Gianpaolo Palo, Luigi Fiorillo, Giuliana Monachino +8

Study Objectives: Polysomnography (PSG) currently serves as the benchmark for evaluating sleep disorders. Its discomfort makes long-term monitoring unfeasible, leading to bias in s…

cs.LG2023★ 1 cited

Bridging AI and Clinical Practice: Integrating Automated Sleep Scoring Algorithm with Uncertainty-Guided Physician Review

Michal Bechny, Giuliana Monachino, Luigi Fiorillo +5

Purpose: This study aims to enhance the clinical use of automated sleep-scoring algorithms by incorporating an uncertainty estimation approach to efficiently assist clinicians in t…