RUDN University neurosurgeon created a method to collect mental activity data of software developers

January 21, 2021

A neurosurgeon from RUDN University studied the mental activity of developers at work. In his novel method, he combined mobile EEG devices and software that analyzes neurophysiological data. The results of the study were published in the materials of the 23rd Euromicro Conference on Digital System Design (DSD).

To collect data about the activity of specific areas of the brain, one can use functional magnetic resonance imaging (fMRI). However, this method involves massive equipment and is only available at clinics or laboratories. Therefore, it is quite difficult to register human mental activity in a natural environment. Even if usual conditions are reproduced in a lab, the very fact that it is an experiment would still affect the behavior of the participants. To study the human brain in everyday situations, for example, at work, scientists need portable technologies, such as devices that would trace EEG through the skin on the head and the bones of the skull. EEG registers the brain's electric activity and the accuracy of this method largely depends on the algorithm used to process the electric signals and to render them into an image. A neurosurgeon from RUDN University confirmed the efficiency of the open-source software solution MNE in the process of EEG interpretation.

"fMRI measures mental activity using blood oxygenation parameters and produces around one image per second, while EEG allows one to collect data with much higher frequency. Moreover, modern-day EEG devices can be used in various situations, unlike fMRI equipment that requires a participant to lie still in a tomographer," said Prof. Aldo Spallone, MD, from the Department of Neurology and Neurosurgery at RUDN University.

MNE is a software solution that has been used in clinical practice to process fMRI and EEG data since 2011. To conduct the experiment, the team invited three groups of developers with different levels of experience. Each group was given a task that had to be completed in 10 to 20 minutes and each participant wore a portable EEG device on their head. The participants worked individually in an open-space office. The team also conducted separate experiments during which the participants worked in pairs and listened to music. Using MNE, the team managed to process EEG data in real-time and obtain images similar to MRI scans. To make the measurements more accurate in the future, Prof. Spallone suggested combining EEF data with MRI and magnetoencephalography results, because EEG is unable to provide information about brain structure.

"It is extremely important to understand how our brain works in different situations. In the case of software developers, it may help create an optimal working environment that would promote high efficiency and reduce the incidence of errors. We have confirmed that EEG devices can be used to study the human brain in everyday conditions. In the future, models of mental activity could be developed based on this method," added Prof. Spallone fron RUDN University.

RUDN University

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