Sonifying ECoG seizure data with overtone mapping: a strategy for creating auditory gestalt from correlated multichannel data

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Terasawa, Hiroko
Parvizi, Josef
Chafe, Chris
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Abstract
This paper introduces a mapping method, harmonic mapping, which projects multichannel time-series data onto a harmonic series structure. Because of the common fate effect of gestalt principle, correlated signals are perceived as a unity, while uncorrelated signals are perceived segregated. This method is first examined with sonification of simple, generic datasets. Then, harmonic mapping is applied to sonification of an ECoG data of an epileptic seizure episode. The relationship between the gestalt formation the correlation in the data across channels is discussed in detail using a 16 channels reduced dataset. Finally, sonification of a 56 channel ECoG dataset is provided to demonstrate the advantage of the harmonic mapping.
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JST-PRESTO
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2012-06
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