4 papers · 1 filter
Deep Sleep Classification via EEG Signal Criticality: A Passive BCI Approach for Sleep-Improvement Neurofeedback
Stanisław Narębski, Tomasz Komendziński, Tomasz M. Rutkowski
Automated sleep staging is a fundamental application of passive Brain-Computer Interfaces (pBCI), decoding spontaneous neural states to enable closed-loop interventions independent…
End-to-End Machine Learning for Depressive State Classification via EEG and fNIRS
Riki Sakurai, Simon Kojima, Mihoko Otake-Matsuura +2
The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conventional methods - relying pri…
Sleep EEG Signal Criticality as a Non-Invasive Predictor of Cognitive Decline in Dementia
Stanisław Narębski, Tomasz Komendziński, Tomasz M. Rutkowski
Early detection of neurodegeneration remains a critical clinical challenge. This study investigates whether sleep EEG signal criticality, quantified via Multifractal Detrended Fluc…
Early Detection of Cognitive Impairment in Elderly using a Passive FPVS-EEG BCI and Machine Learning -- Extended Version
Tomasz M. Rutkowski, Stanisław Narębski, Mihoko Otake-Matsuura +1
Early dementia diagnosis requires biomarkers sensitive to both structural and functional brain changes. While structural neuroimaging biomarkers have progressed significantly, obje…