In this report, we proposed a method for identifying individual characteristics in electroencephalography of the brain of people suffering from chronic migraine during cognitive load. The method is based on a recurrence analysis. The analysis was carried out separately for complex and simple stimuli during cognitive test and comparisons were made between them. This approach makes it possible to identify for each subject the connections between records in which the frequency increases at the time of the cognitive test and/or a stable pattern is formed. The proposed method has a large number of applications in medicine and neurophysiology.
This article describes the developed method for classifying the type of migraine in patients. For this, we analyzed the individual characteristics of patients with different types of migraine when performing cognitive tests. Evoked potentials were used for the analysis when observing the visual stimulus and solving the cognitive test. The cognitive test had different levels of complexity, which made it possible to consider separately the evoked potentials received in solving cognitive tasks of high complexity and separately with a small complexity of the cognitive task. These cases were compared with the case when the evoked potentials were built for all available cognitive tasks. The analysis of the emerging individual characteristics made it possible to determine the trends in the observed evoked potentials in different types of migraine, which makes it possible to more effectively monitor the condition of patients suffering from migraine during treatment.
In this report we proposed a method for identifying the individual characteristics of motor activity based on the recurrence analysis as applied to the encephalography of the human brain. The analysis was carried out according to the real and imaginary movements of the subjects and compared with each other. This approach makes it possible to identify for each subject connections between channels in which the frequency increases at the moment of motor activity and/or a stable pattern corresponding to this movement is formed. The proposed method has a large number of applications in medicine and neurophysiology.
In this article, we proposed a method for identifying the individual characteristics of motor activity based on recurrence analysis as applied to encepholography of the human brain. The analysis was carried out according to the real and imaginary (for the MEG only by imaginary) movements of the subjects and was compared with the background recording when the subject was at rest. This approach allows us to identify channels for each subject in which the frequency increases at the moment of motor activity and / or a stable pattern is formed that corresponds to this movement. The proposed method has a large number of applied applications in medicine and neurophysiology.
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