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IEEE Transactions on Bio-Medical Engineering|October 20, 2025
Direct Quantification of Uncertainty in Deep Learning-Based Automatic Sleep StagingMiika Vainikka, Riku Huttunen, Samu Kainulainen, et al.
IEEE Journal of Biomedical and Health Informatics|March 3, 2025
Optimal Electroencephalogram and Electrooculogram Signal Combination for Deep Learning-based Sleep StagingMasoumeh Tashakori, Matias Rusanen, Tuomas Karhu, et al.
Frontiers in Neurology|April 22, 2024
Excessive daytime sleepiness is associated with relative delta frequency power among patients with mild OSATimothy Howarth, Masoumeh Tashakori, Tuomas Karhu, et al.
Sleep Medicine|April 7, 2024
Interhemispheric differences of electroencephalography signal characteristics in different sleep stagesMasoumeh Tashakori, Matias Rusanen, Tuomas Karhu, et al.
Pulmonology|June 12, 2026
Hypnodensity sleep metrics from fingertip photoplethysmography are better associated with daytime sleepiness and fatigue than traditional metrics from polysomnographyMatias Rusanen, Viateur Tuyinsenge, Sandrine Muller, et al.
Journal of Sleep Research|October 24, 2024
A comparative analysis of unsupervised machine-learning methods in PSG-related phenotypingMohammadreza Ghorvei, Tuomas Karhu, Salla Hietakoste, et al.
Journal of Sleep Research|July 3, 2023
Self-applied somnography: technical feasibility of electroencephalography and electro-oculography signal characteristics in sleep staging of suspected sleep-disordered adultsMatias Rusanen, Henri Korkalainen, Heidur Gretarsdottir, et al.
IEEE Journal of Biomedical and Health Informatics|April 6, 2023
Generalizable Deep Learning-Based Sleep Staging Approach for Ambulatory Textile Electrode Headband RecordingsMatias Rusanen, Riku Huttunen, Henri Korkalainen, et al.
Journal of Sleep Research|May 31, 2026
Participation in Sleep Europe Conferences: Insights From Early Career ProfessionalsMonisha Ravikumar, Michaela Pawley, Anna M Biller, et al.
Journal of Sleep Research|October 23, 2024
Retrospective validation of automatic sleep analysis with grey areas model for human-in-the-loop scoring approachMatias Rusanen, Gabriel Jouan, Riku Huttunen, et al.
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