January 24, 2019
AI & Industry 4.0
Ciklum News

Ciklum’s AI Experts Release A Scientific Study On Brain Activity

Ciklum’s AI Experts Release A Scientific Study On Brain Activity

Ciklum’s AI technical lead, Anton Popov, and IoT research engineer, Ivan Seleznov, along with five other researchers published a scientific study “Electroencephalograms during Mental Arithmetic Task Performance” in a special issue of Big Data and Digital Health on January 18th, 2019.

The seven researchers from Kyiv, Ukraine and Osaka, Japan conducted an investigation into electroencephalogram (EEG) Fourier power spectral, coherence and detrended fluctuation characteristics during performance of mental tasks. In neuroscience the activation of cognitive function is studied by spectral and coherence analysis. Anton with the group of researchers decided to go further and explore the new possibilities of nonlinear digital signal processing techniques such as detrended fluctuations and entropy by collecting electroencephalogram data from subjects performing cognitive tasks.

The researchers recruited 36 student volunteers and took the participants through a series of arithmetic tasks. This was accompanied by inducing changes in their emotional states, so this study also addresses brain activity dynamics during evoked emotions. Based on the accuracy of the computations the recordings were divided into optimal and sub-optimal (when mental tasks required additional efforts).

Anton Popov
Understanding a brain’s computational activity while it performs various mental tasks enables us to get a closer look at the brain’s architecture. The recordings we made can be used for studying the involvement of different brain areas in cognition processes and nonlinear characteristics of brain dynamics.
Anton Popov, AI technical lead at Ciklum

EEG data collection

The organization of EEG data collection during the experiment. Bounding boxes depict the two EEG recordings stored in the database.

You can read the full article by the link:

All the recordings are available through the Physiobank platform and can be used by the neuroscience research community to study brain dynamics during cognitive workloads and emotional experiences.

About Anton Popov

Anton Popov is the Artificial Intelligence/Deep Learning technical lead at Ciklum with 15+ years of experience in the development and implementation of biosignal analysis and classification algorithms. He is affiliated with Igor Sikorsky Kyiv Polytechnic Institute as an Associate Professor. Since 2002, Anton has been a member of the IEEE Engineering in Medicine and Biology Society, has published 100+ papers and is currently supervising 8 PhD students.

Anton’s awards include:

  • Outstanding IoT Project Award at the 2018 Computing’s Big Data Excellence Awards,
  • Gold medal at the 30th Politzer Society Meeting at World Congress of Otology (Niigata, Japan) in the fields of otology and neurotology,
  • Gold medal at the 30th Politzer Society Meeting award in the fields of otology and neurotology,
  • 2014 Intel Business Challenge Europe Finals (Vilnius, Lithuania).

About Ivan Seleznov

Ivan Seleznov is an IoT Research Engineer at Ciklum with 5+ years of experience in embedded solutions and 4+ years in the development and implementation of biomedical signal analysis and classification algorithms. He graduated from Igor Sikorsky Kyiv Polytechnic Institute with a Master’s degree in biomedical signal analysis. In 2015, Ivan co-founded  “OpenWorld” to aid visually impaired people navigate in city spaces.


Read also: Ciklum R&D won Gold Medal at the World Congress of Otology in Japan