Spiros Michalakopoulos

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A combinatorial model for analyzing and interpreting an electrocardiogram (ECG) was presented in [Allali et al. '10] and [Iliopoulos &#38; Michalakopoulos '09 and '10]. An application of the model is <i>QRS</i> peak detection and the resulting algorithm was shown to be space, as well as time efficient. Experimental results on the MIT-BIH Arrhythmia database(More)
Three problems that arise from electrocardiogram (ECG) interpretation and analysis are presented, followed by algorithmic solutions based on a combinatorial model. First, the beat classification problem is discussed and possible solutions are investigated. Secondly, given the R R-intervals, which can be determined using this combinatorial model, or any Q R(More)
An interesting problem in music information retrieval is to classify songs according to rhythms. A rhythm is represented by a sequence of “Quick” (Q) and “Slow” (S) symbols, which correspond to the (relative) duration of notes, such that S = 2Q. Christodoulakis et al. presented an efficient algorithm that can be used to classify musical sequences according(More)
The problem of classifying dance songs according to rhythms has recently been introduced in [4] and [3]; in this paper, we present new efficient algorithms that take into account temporal errors, which could not be handled by the algorithms presented in [4] and [3]. We analyze and compare the running times of two algorithmic variants and furthermore show(More)
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