Creating Biosignal Algorithms for Musical Applications from an Extensive Physiological Database
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Date
2015
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NIME
Abstract
Previously the design of algorithms and parameter calibration for biosignal music performances has been based on testing with a small number of individuals - in fact usually the performer themselves. This paper uses the data collected from over 4000 people to begin to create a truly robust set of algorithms for heart rate and electrodermal activity measures, as well as the understanding of how the calibration of these vary by individual.
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Keywords
Biosignals, EDA, HR, feature extraction, database, physiological signals, EDAtool, HRtool