Department of Health Technologies

Head of the research group:  Professor MAIE BACHMANN,
Members: Hiie Hinrikus, Jaanus Lass,  Laura Päeske
Doctoral students: Tuuli Uudeberg, Safoora Masoumirad
Consultant: Toomas Põld (Meliva)
 

Topics and competences
Keywords: signal processing, electroencephalography, brain disorders, transcranial direct current stimulation

The research group is experienced in the interdisciplinary area of information technology and brain physiology. The studies are aimed to detect and interpret the features in the brain electroencephalography (EEG) signal characteristic for mental disorder, occupational and/or environmental stressors comprising the advanced methods of signal analysis and the knowledge about brain neuronal activity. An original Spectral Asymmetry Index (SASI) has been developed and proved as a promising method in various applications.

Selected results:

• By applying EEG-based objective measures it is feasible to indicate early symptoms of depressioon, but also the changes and recovery caused by mRNA COVID-19 vaccine;
• Different EEG markers reflect partly the same features in brain functioning, while Higuchi’s fractal dimension reveals the widest scale of EEG features among the studied markers;
• Developed EEG based in phase matrix profile outperforms Higuchi’s fractal dimensioon in detecting major depressive disorder;
• Decreased small-world organization of a brain network is compensated with increased alpha connectivity;
• There is no threshold for the biological or health effects of radio frequency radiation, while the health risk can be minimized by linking the health protection limit values to the level of radiation, in which no significant health effects have been noticed during a long period of exposure (6 V/m).
   

Selected projects:

• TK218U8 “The Centre of Excellence for Well-Being Sciences” (2024-2030);
• TAR16013 (EXCITE) (TK148) "Estonian Centre of Excellence in ICT Research" (2016−2023);
• AR20013IHW „FinEst Piloting Programme by FinEst Centre for Smart Cities project "Urban Planning Well-being Score for Good Quality Living Environment"“ (2022-2023)
• 5GEMF1 "Assessment of current and 5G caused possible health effects related to nonionizing radiation" (2021−2022)

Selected articles

• Uudeberg, T.; Belikov, J.; Päeske, L.; Hinrikus, H.; Liiv, I.; Bachmann, M. (2024). In-phase matrix profile: A novel method for the detection of major depressive disorder. Biomedical Signal Processing and Control, Art. no.105378−8 pp. DOI: 10.1016/j.bspc.2023.105378. 
• Päeske, L.; Uudeberg, T.; Hinrikus, H.; Lass, J.; Bachmann, M. (2023). Correlation between electroencephalographic markers in the healthy brain. Scientific Reports, 13, #6307. DOI: 10.1038/s41598-023-33364-z. 
• Põld, T.; Päeske, L.; Hinrikus, H.; Lass, J.; Bachmann, M. (2023). Temporal stability and correlation of EEG markers and depression questionnaires scores in healthy people. Scientific Reports, 13, 21996. DOI: 10.1038/s41598-023-49237-4
• Hinrikus, H.; Koppel, T.; Lass, J.; Roosipuu, P.; Bachmann, M. (2023). Limiting exposure to radiofrequency radiation: the principles and possible criteria for health protection. International Journal of Radiation Biology, 99 (8), 1167−1177. DOI: 10.1080/09553002.2023.2159567.
• Bachmann, M.; Päeske, L.; Kalev, K.; Aarma, K.; Lehtmets, A.; Ööpik, P.; Lass, J.; Hinrikus, H. (2018). Methods for classifying depression in single channel EEG using linear and nonlinear signal analysis. Computer Methods and Programs in Biomedicine, 155, 11−17.10.1016/j.cmpb.2017.11.023.
• Hinrikus, H.; Bachmann, M.; Lass, J. (2018). Understanding physical mechanism of low-level microwave radiation effect. International Journal of Radiation Biology, 94 (10), 877−882.10.1080/09553002.2018.1478158.