Abstract
This contribution describes a classification technique that improves the heart rate estimation during hemodialysis treatments. After the heart rate is estimated from the pressure signal of the dialysis machine, a classifier decides if it is correctly identified and rejects it if necessary. As the classifier employs a support vector machine, special interest is put on the automatic selection of its user parameters. In this context, a comparison between different optimization techniques is presented, including a gradient projection method as latest development.
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Vogt, M., Moissl, U., Schaab, J. (2006). Heart Rate Classification Using Support Vector Machines. In: Spiliopoulou, M., Kruse, R., Borgelt, C., Nürnberger, A., Gaul, W. (eds) From Data and Information Analysis to Knowledge Engineering. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31314-1_88
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DOI: https://doi.org/10.1007/3-540-31314-1_88
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