Change in Frequency Modulation of Electroencephalographic Activity in Imaginary and Real Limb Movement

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Abstract

INTRODUCTION: Investigation of electroencephalographic activity as a marker of cognitive processes in the brain traditionally focuses on the analysis in the frequency domain considering rhythms of encephalogram (EEG) as potential carriers of information needed for research. At the same time, analysis of the EEG frequency modulation effects requires improvement of approaches in the field of digital signal processing. Taking into account the fact that frequency modulation of EEG, as well as amplitude modulation, can be a marker of a number of states, it seems promising to develop a method for detecting this phenomenon and using it to evaluate a number of parameters of the brain dynamics associated with biological feedback systems. AIM: To evaluate the phenomena of frequency modulation when the user performs tasks associated with the control of external devices based on the brain–computer interface, implemented in the phenomena of electrical activity in the motor cortex area.

MATERIALS AND METHODS: To obtain the data, a group of thirty volunteers of both genders aged 17 to 23 years was formed. The participants of the experiment had to execute four commands and repeat them in an unknown order set by the program. The experiment was conducted in two ways: physically and mentally. That is, in the first method, each command corresponded to a certain movement of a person, in the second — the same commands were executed in imagination, the movement was imagined mentally. The command was considered successfully executed if the volunteer managed to repeat and hold the position set by the program for two seconds.

RESULTS: Based on the developed method for evaluating the frequency modulation of the EEG, the dynamics of the electrical activity of the brain was studied in the range of 9 Hz to 12 Hz when a user was performing real and imaginary movements. A comparative analysis showed that the differences were mostly recorded in the condition when the subject did not achieve the goal. At the same time, the differences to a greater extent were observed in the experiments where the subject had to make real, rather than imaginary movements. The significant differences between low- and high-frequency modulations were associated with the inability for the user to generate the requested command, which he could see by the biofeedback mechanism. It has been established that the greater the number of high-frequency restructures observed on the EEG, the smaller number of low-frequency restructures occur at the same epoch of analysis.

CONCLUSION: The results obtained considerably expand the understanding of the mechanisms of frequency modulation of the EEG. In general, the methods and algorithms underlying the analysis that permitted their identification can be used to solve a wide range of tasks related to processing of EEG signals, including improvement of methods for detecting user errors by EEG when controlling brain-computer interface devices.

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About the authors

Yaroslav А. Тurovskiу

Voronezh State University; V. A. Trapeznikov Institute of Control Sciences

Author for correspondence.
Email: yaroslav_turovsk@mail.ru
ORCID iD: 0000-0002-5290-885X
SPIN-code: 6494-4501

MD, Cand. Sci. (Med.), Dr. Sci. (Tech.), Associate Professor

Russian Federation, Voronezh; Moscow

Anastasiya S. Davydova

Voronezh State University

Email: asya.dinastija@yandex.ru
ORCID iD: 0000-0001-8546-0986
SPIN-code: 5288-8737
Russian Federation, Voronezh

Viktor Yu. Alekseyev

Voronezh State University

Email: Quindecim413@mail.ru
ORCID iD: 0000-0002-4541-9978
SPIN-code: 8689-7496
Russian Federation, Voronezh

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Supplementary files

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2. Fig. 1. Presentation of the program at the calibration stage.

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3. Fig. 2. Presentation of the program at the examination stage.

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4. Fig. 3. Evaluation of the peak–to-peak sequence for the EEG signal filtered using the Fourier transform in the frequency range of 9 Hz–12 Hz.

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5. Fig. 4. An example of variability of the period of peaks of electroencephalogram filtered from F3 channel in the frequency range of 7 Hz–10 Hz in execution by a user the ‘Right’ command.

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6. Fig. 5. Differences between the number of cases of low-frequency modulation and high-frequency modulation.

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7. Fig. 6. Results of cluster analysis of frequency modulations of the electroencephalogram.

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Media Registry Entry of the Federal Service for Supervision of Communications, Information Technology and Mass Communications (Roskomnadzor) PI No. FS77-76803 dated September 24, 2019.



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