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The physiological analysis of electroencephalogram (EEG) signals is of great significance in assessing the activity of the brain function and the physiological state. EEG is a means of clinical examination of brain diseases. Age is one of the important factors that affect the results of the EEG. EEG signal analysis is mainly to analyze the time series of the signal, multiscale entropy (MSE) analysis...
Movement primitive segmentation enables long sequences of human movement observation data to be segmented into smaller components, termed movement primitives, to facilitate movement identification, modeling, and learning. It has been applied to exercise monitoring, gesture recognition, human–machine interaction, and robot imitation learning. This paper proposes a segmentation framework to categorize...
Complexity of RR intervals can be measured by Sample entropy (SampEn) traditionally estimated only for a limited number of points by fixing the values of the embedding dimension "m" and distance threshold "r". Recently we have proposed a new and fast Norm Component Matrix (NCM) algorithm for SampEn calculation — it allows analyzing whole ranges of (m, r) values leading to entropy...
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