SIGNAL ANALYSIS: TOOLS FOR DETECTING FEATURE POINTS IN WAVEFORM
Abstract
One of the targets of signal processing is the feature identification of signal under test in such a way that it allows the measurement of important parameters related to the analyzed waveform. In this sense the so called noticeable or fiducial points are considered, i.e. maxima, minima, onsets and offsets and other ones of interest. Still in ideal conditions to get some of these points might be relatively involved. In the presence of noise such process is even more complicated.
The authors of this paper have developed a tool called "curvature filters" which makes possible to capture, in an one-dimensional array, on the presence of noise, the more highlighting changes in a signal, getting the onsets, offsets and local peaks, with a taskforce easier in comparison with current methods. These issues has been reported by the authors in previous published works.
In the present report emphasis is targeted in the behavior in face to noise of the proposed process, summarizing application examples in the characterization of electrocardiographic signals. The procedure is simulated in Matlab and GNU Octave by using test signals from the MIT medical database, Cardiosim II equipment patterns and synthetic signals developed by the authors.
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