Summary
This paper presents algorithms that provide support in the task of reviewing the physiological parameters recorded during a polysomnography, the gold standard test for the diagnosis of Sleep Apnea-Hypopnea Syndrome (SAHS). This support is obtained through the generation of visual metaphors which help identify events (apneas, hypopneas and desaturations) that occur over the span of the recording and are relevant to the diagnosis of SAHS.
The definition of these events is not completely standardized and it is not unusual that different physicians use different criteria when identifying them. To tackle this problem our algorithms start with a linguistic description of the events to be identified. This description is obtained directly from the clinical staff and is projected onto a set of algorithms of a structural nature that support the generation of the visual metaphors. To represent and manipulate the imprecision and vagueness characteristic of medical knowledge we rely on the fuzzy set theory.
The metaphors proposed herein have been implemented in a tool aimed at supporting the diagnosis of SAHS. The tool provides wizards that permit the morphological criteria that define the apneas, hypopneas and desaturations to be customized by the physician and the visual metaphors automatically reflect the new criteria.
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Otero, A., Félix, P., Zamarrón, C. (2009). Visual Knowledge-Based Metaphors to Support the Analysis of Polysomnographic Recordings. In: Corchado, J.M., De Paz, J.F., Rocha, M.P., Fernández Riverola, F. (eds) 2nd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2008). Advances in Soft Computing, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85861-4_2
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DOI: https://doi.org/10.1007/978-3-540-85861-4_2
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