Finding Intuitive Abstractions of High-Frequency Data

In this paper we describe ways to transform a curve constituted by a series of data points delivered by monitoring devices into a series of bends and lines between them. The resulting qualitative representation of the curve can easily be utilized in a Knowledge Based System. Since the representation obtained resembles the way humans describe curves, e.g. ``this bend is not sharp enough to be normal'', the transformation of the data described in this paper promises to facilitate knowledge acquisition in the eld of interpreting high-frequency data in the medical domain. Our analysis performs best on curves that are periodical but too irregular to be analyzed by Fast Fourier Transformation or other standard methods.