Sami Myllymaa
Visiting Researcher
Senior Researcher
Docent (Medical Physics, especially Biomaterials and Bioelectrode Technology)
Co-head of the Sleep Technology and Analytics Group (STAG)
sami.myllymaa@uef.fi | +358 40 557 2499
Adjunct professor Sami Myllymaa received his Ph.D. degree in 2010 and the title of docent in the field of Medical Physics, especially biomaterials and bioelectrode technology in 2014 from the University of Eastern Finland. He is currently acting as a Senior Researcher and Co-head of the Sleep Technology and Analytics Group (STAG) at the Department of Applied Physics, University of Eastern Finland.
His current research is focused on development of novel wearable sensors and machine learning solutions for personalized diagnostics and prognostics of sleep disorders (obstructive sleep apnoea, sleep bruxism). Furthermore, he has been very active in the field of salivary metabolomics and development of new coatings and electrochemical biosensors for point-of-care diagnostics. In addition to scientific publications, his work has led to commercialization of the scientific innovations. He involved to the development of an EEG electrode set for emergency medicine. This BrainStatus EEG-electrode set (Bittium Corp.) is patented, CE-approved and currently marketed globally (https://www.bittium.com/products_services/medical/bittium_brainstatus).
Research groups
Publications
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Acute cardiorespiratory coupling impairment in worsening sleep apnea-related intermittent hypoxemia
Hietakoste, Salla; Armanac-Julian, Pablo; Karhu, Tuomas; Bailon, Raquel; Sillanmäki, Saara; Töyräs, Juha; Leppänen, Timo; Myllymaa, Sami; Kainulainen, Samu. 2023. IEEE transactions on biomedical engineering. 2024; 71: 326-333 -
Experimental Comparison of Thin Film Surfaces to Detect Oral Salivary Biomarkers by Surface-Enhanced Raman Spectroscopy
Hurskainen, Miia; Korhonen, Hannu; Myllymaa, Sami; Lappalainen, Reijo. Teoksessa: Dekhtyar, Yuri; Saknite, Inga(toim.) , 2023. 19th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics: Proceedings of NBC 2023, June 12–14, 2023, Liepaja, Latvia. s. 269-277. Springer -
Generalizable Deep Learning-based Sleep Staging Approach for Ambulatory Textile Electrode Headband Recordings
Rusanen, Matias; Huttunen, Riku; Korkalainen, Henri; Myllymaa, Sami; Toyras, Juha; Myllymaa, Katja; Sigurdardottir, Sigridur; Olafsdottir, Kristin Anna; Leppanen, Timo; Arnardottir, Erna Sif; Kainulainen, Samu. 2023. IEEE journal of biomedical and health informatics. 27: 1869-1880 -
Novel 3D printed probe for bioimpedance spectroscopic measurement of oral mucosa: design and testing with ex vivo porcine oral tissues
Emran, Shekh; Jokinen, Noora; Laitinen, Kimmo; Lappalainen, Reijo; Myllymaa, Sami. 2023. Measurement science and technology. 34: -
Self‐applied somnography: technical feasibility of electroencephalography and electro‐oculography signal characteristics in sleep staging of suspected sleep‐disordered adults
Rusanen, Matias; Korkalainen, Henri; Gretarsdottir, Heidur; Siilak, Tiina; Olafsdottir, Kristin Anna; Töyräs, Juha; Myllymaa, Sami; Arnardottir, Erna Sif; Leppänen, Timo; Kainulainen, Samu. 2023. Journal of sleep research. [Epub ahead of print 03 July 2023]: . e13977 -
Towards a Deeper Understanding of Sleep Stages through their Representation in the Latent Space of Variational Autoencoders
Biedebach, Luka; Rusanen, Matias; Pórðarson, Benedikt Hólm; Arnardóttir, Erna Sif; Óskarsdóttir, María; Nikkonen, Sami; Korkalainen, Henri; Myllymaa, Sami; Töyräs, Juha; Kainulainen, Samu; Leppänen, Timo; Islind, Anna Sigridur. Teoksessa: Bui, Tung(toim.) , 2023. Proceedings of the 56th Annual Hawaii International Conference on System Sciences. s. 3111-3120. Hawaii International Conference on System Sciences -
A Comparison of Signal Combinations for Deep Learning-Based Simultaneous Sleep Staging and Respiratory Event Detection
Huttunen, Riku; Leppanen, Timo; Duce, Brett; Arnardottir, Erna S.; Nikkonen, Sami; Myllymaa, Sami; Toyras, Juha; Korkalainen, Henri. 2022. IEEE transactions on biomedical engineering. [Date of Publication: 28 November 2022]: 1-12 -
ABOSA – Freely available automatic blood oxygen saturation signal analysis software: Structure and validation
Karhu, Tuomas; Leppänen, Timo; Töyräs, Juha; Oksenberg, Arie; Myllymaa, Sami; Nikkonen, Sami. 2022. Computer methods and programs in biomedicine. 226: -
Deep Learning Enables Accurate Automatic Sleep Staging Based on Ambulatory Forehead EEG
Leino, Akseli; Korkalainen, Henri; Kalevo, Laura; Nikkonen, Sami; Kainulainen, Samu; Ryan, Alexander; Duce, Brett; Sipila, Kirsi; Ahlberg, Jari; Sahlman, Johanna; Miettinen, Tomi; Westeren-Punnonen, Susanna; Mervaala, Esa; Toyras, Juha; Myllymaa, Sami; Leppanen, Timo; Myllymaa, Katja. 2022. IEEE access. 10: 26554-26566 -
Desaturation event scoring criteria affect the perceived severity of nocturnal hypoxic load
Karhu, Tuomas; Leppänen, Timo; Korkalainen, Henri; Myllymaa, Sami; Duce, Brett; Töyräs, Juha; Nikkonen, Sami. 2022. Sleep medicine. 100: 479-486