A Brain Computer Interface (BCI) enables to get electrical signals from the brain. In this paper, the research type of BCI was non-invasive, which capture the brain signals using electroencephalogram (EEG). EEG senses the signals from the surface of the head, where one of the important criteria is the brain wave frequency. This paper provides the measurement of EEG using the Emotiv EPOC headset and applications developed by Emotiv System. Two types of the measurements were taken to describe brain waves by their frequency. The first type of the measurements was based on logical and analytical reasoning, which was captured during solving mathematical exercise. The second type was based on relax mind during listening three types of relaxing music. The results of the measurements were displayed as a visualization of a brain activity.
Brain-computer interface (BCI) is a device that enables the connection between the human brain and a computer, therefore, it allows us to observe the brain activity. The goal of this article is to prove that brain-computer interface is a helpful and quite precise tool. This goal will be achieved by presenting various examples from real-life situations. The results show that this device is indeed helpful, e.g. in a medical field, however, it is not commonly used in hospitals.
The aim of this study is to present and summarize our numerical algorithm for the determination of stability charts in the delay space for linear time-invariant time systems with constant delays (TDS), both retarded and neutral ones. The core of algorithm lies in a successive (iterative) approximation of the infinite-dimensional characteristic quasi-polynomial in each grid node of the delay space. This approximation resulting in a polynomial or an exponential polynomial with commensurate delays is made in the neighborhood of the dominant characteristic value (pole) that has recently been estimated in the closest grid node. Two different approximation techniques are presented; namely, continuous-time and discrete-time ones. A complete numerical example for retarded TDS is presented, whereas the approximation issues are highlighted in another example for neutral TDS.
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