Title :
A spline framework for ECG analysis
Author :
Guilak, Farzin G. ; McNames, James
Author_Institution :
Biomedical Signal Processing Laboratory in the Department of Electrical and Computer Engineering at Portland State University, Portland, Oregon, USA
fDate :
Aug. 30 2011-Sept. 3 2011
Abstract :
In this effort we introduce a spline framework for ECG waveform analysis, with initial application to the ECG delineation (segmentation) problem. The framework comprises knot initialization, spline interpolant, error metric, and knot location optimization to parametrically represent the waveform for analysis, classification, or compression. Choice of these constituents is driven by the application of the framework. For our initial application of ECG delineation, we use the framework to identify characteristic points corresponding to waveform onset and offset times, peak values, and junction points. These are represented mathematically as critical points and points of inflection, which serve as knot locations for linear or cubic Hermite interpolants in the framework. Preliminary tests on a limited but diverse set of morphologies from the European ST-T database indicate that the framework obtains knot locations corresponding to characteristic points, and the resultant interpolated waveform represents the original signal well with low mean squared error.
Keywords :
Algorithm design and analysis; Computers; Electrocardiography; Genetic algorithms; Hidden Markov models; Optimization; Spline; Algorithms; Brain; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Humans; Models, Neurological; Numerical Analysis, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2011.6090216