Abstract
Introduction: Methods of detecting the start of a movement and moments of movement planning are important in neuroscience. Using the signals of electrical activity of muscles (electromyograms) in order to precisely detect the moment of movement is a special problem, because the initial signals are complex, non-stationary and affected by noise. It is especially important in experiments with simultaneous registration of an EEG and an electromyogram, when you have to analyze the interaction between brain structures.Purpose: Development of methods for electromyogram data analysis and techniques for their use in a detailed study of motor activity.Methods: We use the threshold detection method based on calculating the derivative of the original signal filtered and smoothed. Such an approach makes it possible to estimate the starting points of the onset of motion relatively quickly and accurately, even along a part of a time series.Results: We have developed a technique which allows you to automatically detect the precursor of a movement start, based on the analysis of electromyographic signals. We have calculated the distribution of the delay between the presentation of a sound signal and the beginning of a movement, and evaluated the statistical properties of this distribution.Practical relevance: The results of this research can be used to automatically detect starting points in experiments with simultaneous EEG recording, and later be applied to solve practical problems related to the development of controlled prostheses for the rehabilitation of people with disabilities.
Published Version
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