@inbook{5948df064613471abca3fd0132216ec2,

title = "Time Series Clustering Algorithm for Two-Modes Cyclic Biosignals",

abstract = "In this study, an automatic algorithm which computes ameanwaveis introduced. Themeanwaveis produced by averaging all cycles of a cyclic signal, sample by sample. With that information, the signal{\textquoteright}s morphology is captured and the similarity among its cycles is measured. A k-means clustering procedure is used to distinguish different modes in a cyclic signal, using the distance metric computed with themeanwaveinformation. The algorithm produced is signal-independent, and therefore can be applied to any cyclic signal with no major changes in the fundamental frequency. To test the effectiveness of the proposed method, we{\textquoteright}ve acquired several biosignals in context tasks performed by the subjects with two distinct modes in each. The algorithm successfully separates the two modes with 99.3% of efficiency. The fact that this approach doesn{\textquoteright}t require any prior information and its preliminary good performance makes it a powerful tool for biosignals analysis and classification.",

keywords = "clustering, signal-processing, data mining, unsupervised learning, Biosignals, waves",

author = "Gamboa, {Hugo Filipe Silveira}",

year = "2013",

month = jan,

day = "1",

language = "Unknown",

isbn = "978-3-642-29751-9 / 978-3-642-29752-6",

series = "Communications in Computer and Information Science",

publisher = "Springer Berlin Heidelberg",

number = "273",

pages = "233--245",

editor = "Ana Fred and Joaquim Filipe and Hugo Gamboa",

booktitle = "Biomedical Engineering Systems and Technologies",

}