Health and Wellness Measurements


Health & Wellness Measurements group

Multimodal brain imaging

We are the first research group in the world that has enabled measurements of blood pressure and cardiorespiratory signals in magnetic neuroimaging environments, particularly simultaneously with Magnetoencephalography (MEG) (Myllylä et al. 2017a) and Magnetic Resonance Imaging (MRI) (Myllylä et al 2011).


On the left, MEG multimodal setup. On the right, averaged responses of breath holds for different signal modalities (Figs. a-e) in human body and the brain, recorded with MEG multimodal setup. Fig. (f) shows an averaged response for magnetic resonance encephalography (MREG) when using the same breath hold task, recorded in MRI multimodal setup (Myllylä et al. 2017a, Korhonen et al. 2014). 

One of our main focuses is on brain research and development of these related imaging techniques, also for wearable use. The study activities are conducted in close collaboration with Oulu Functional Neuroimaging group (OFNI), located also in University of Oulu. We combine existing and novel brain sensing techniques. Currently, optical, capacitive and microwave based imaging techniques are under development.

Measurement volume of the developed capacitive brain sensor (Myllylä et al. 2017b), capable of reaching ~2 cm depth. (CSF = Cerebrospinal fluid, GM = Grey matter, WM = White matter).

In particular, one of the special focuses is on brain clearance mechanism and the glymphatic system (Zienkiewicz et al. 2017). Using the combined techniques we can measure, such as, cerebral hemodynamics, blood volume and flow, water dynamics in the brain cortex and changes in dielectric properties of brain tissue (Myllylä et al. 2017b). These techniques can be utilized for detecting such as brain hematomas and edema, pain, stages of sleep. Furthermore, these techniques are extensively utilized in several brain research areas conducted together with collaborating partners in USA, Europe and Asian.

Our group joined the world’s first measurements on blood brain barrier disruption (BBBD) in human, which were performed using combined NIRS/EEG technique in Oulu University Hospital (Kiviniemi et al. 2017).


Wearable sensors and wellness measurements

In addition to brain imaging, we employ and develop different wearable biomedical sensors to acquire data on human health and wellness in clinical and home environments. For instance, for muscle contraction measurement we use a combined surface electromyography (sEMG), NIRS and acceleration measurement technique (Kauppi et al. 2016). For accurate measurement of human body balance we utilize the latest MEMS sensing techniques (Sanz et al. 2016).

One of the current projects in human wellness measurements is the Bulstop project to prevent school violence by utilizing wearable sensor technology.  So far, the school violence detection is based on movement, electrocardiography (ECG), speech and electroencephalography (EEG). We have conducted several school violence simulations in Finland, Indonesia, and China with promising results.

Based on the collected data, violence event was detected from ECG signal with accuracy around 95%.  The ECG signal is analyzed with the Bivariate Empirical Mode Decomposition (BEMD). Based on the movement, we can distinguish normal daily activities from movement related to violence with accuracy up to 90% (Ferdinando et al. 2017).

Wellness measurements include also monitoring the environment we are living. Using wearable and/or small sensors we can measure different environmental parameters that may affect human wellness e.g. noise, lightning or water quality (Hakala & Myllylä 2016). Further, we can study how these affect human health.

Our main research collaborators 

Oulu University Hospital and Medical Research Center, Oulu, Finland
University Hospital Charité, Germany
Dongseo University, Busan, Korea
Harbin Institute of Technolgy, Harbin, China
Petra Christian University, Surabaya, Indonesia
Radboud University Medical Center, Nijmegen, Netherlands
Leibniz Institute for Neurobiology, Magdeburg, Germany
Gdansk University of Technology, Gdańsk, Poland
Saratov State University, Saratov, Russia
University of Luleå, Sweden
University of Umeå, Sweden
GE Health care, Finland


Myllylä T, Zacharias N, Korhonen V, Zienkiewizc A,  Hinrichs H, Kiviniemi V, Walter M (2017) Multimodal brain imaging in magnetoencephalography: a method for measuring blood pressure and cardiorespiratory oscillations. Scientific Reports 7, Article number: 172 (2017).

Myllylä T, Elsoud AA, Sorvoja H, Myllylä R, Harja J, Nikkinen J, Tervonen O, Kiviniemi V (2011) Fibre optic sensor for non-invasive monitoring of blood pressure during MRI scanning. J. Biophoton. 4 (1–2): 98–107.

Korhonen V, Hiltunen T, Myllylä T, Wang X, Kantola J, Nikkinen J, Zang Y, LeVan P, Kiviniemi V (2014) Synchronous multi-scale neuroimaging environment for critically sampled physiological analysis of brain function- a Hepta-scan concept. Brain Connectivity, Nov;4(9):677-89.

Myllylä T, Vihriälä E, Pedone M, Korhonen V, Surazynski L, Wróbel M, Zienkiewicz A, Hakala J, Sorvoja H, Lauri J, Fabritius T, Jędrzejewska-Szczerskae M, Kiviniemi V, Meglinski I (2017) Prototype of an opto-capacitive probe for non-invasive sensing cerebrospinal fluid circulation, Invited Paper, Proc. SPIE 10063.

Zienkiewicz A, Huotari N, Raitamaa L, Raatikainen V, Ferdinando H, Vihriälä E, Korhonen V,  Myllylä T, Kiviniemi V (2017) Continuous blood pressure recordings simultaneously with functional brain imaging - studies of the glymphatic system, Proc. SPIE 10063, Dynamics and Fluctuations in Biomedical Photonics XIV, 1006311 (March 3, 2017); doi:10.1117/12.2252032

Kiviniemi V, Korhonen V, Kortelainen J, Rytky S, Keinänen T, Tuovinen T, Isokangas M, Sonkajärvi E, Siniluoto T, Nikkinen J, Alahuhta S, Tervonen O, Turpeenniemi-Hujanen T, Myllylä T, Kuittinen O, Voipio J (2017) Real-time monitoring of human blood-brain barrier disruption. PLoS ONE 12(3):e0174072.

Kauppi K, Korhonen V, Ferdinando H, Kallio M, Myllylä T (2017) Combined surface electromyography, near-infrared spectroscopy and acceleration recordings of muscle contraction: the effect of motion, Journal of Innovative Optical Health Sciences, Vol. 10, No. 2 (2017) 1650056 (13 pages).

Sanz Morère C, Surazynski L, Pérez-Tabernero A, Vihriälä E, Myllylä T, “MEMS technology sensors as a more advantageous technique for measuring foot plantar pressure and balance in human,” Journal of Sensors, vol. 2016, Article ID 6590252, 9 pages (2016).

Ferdinando, H., Guobing Sun, Tian Han, Zhu Zhang, Liang Ye, Tuija Huuki, Seppo Laukka, Tapio Seppänen, Esko Alasaarela (2017) School Violence Detection Using Movement Recognition and Affective Computing. In review

Hakala J. & Myllylä T., "Optical probe utilizing the cross beam method for measuring solids," Opt. Eng. 55(8), 080501 (2016).



Viimeksi päivitetty: 9.6.2017