TY - EDBOOK AB -

We introduce a novel approach in EEG data sonification for process monitoring and exploratory as well as comparative data analysis. The approach uses an excitory/articulatory speech model and a particularly selected parameter mapping to obtain auditory gestalts (or auditory objects) that correspond to features in the multivariate signals. The sonification is adaptable to patient-specific data patterns, so that only characteristic deviations from background behavior (pathologic features) are involved in the sonification rendering. Thus the approach combines data mining techniques and case-dependent sonification design to give an application-specific solution with high potential for clinical use. We explain the sonification technique in detail and present sound examples from clinical data sets. DA - 2006 KW - thermann LA - eng PY - 2006 TI - Vocal Sonification of Pathologic EEG Features UR - https://nbn-resolving.org/urn:nbn:de:0070-pub-20172912 Y2 - 2024-11-25T04:06:14 ER -