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Algorithms for Extracting Mental Activity Phases from Heart Beat Rate Streams

P. 113–125.
Dubatovka A., Mikhailova E., Zotov M., Novikov B.

 The paper presents algorithms for automatic detection of non-stationary periods of cardiac rhythm during professional activity. While working and subsequent rest operator passes through the phases of mobilization, stabilization, work, recovery and the rest. The amplitude and frequency of non-stationary periods of cardiac rhythm indicates the human resistance to stressful conditions. We introduce and analyze a number of algorithms for non-stationary phase extraction: the different approaches to phase preliminary detection, thresholds extraction and final phases extraction are studied experimentally. These algorithms are based on local extremum computation and analysis of linear regression coefficient histograms. The algorithms do not need any labeled datasets for training and could be applied to any person individually. The suggested algorithms were experimentally compared and evaluated by human experts.
 

Language: English
DOI
Text on another site
Keywords: pattern recognitionmental activity phasesSignal processingData stream Linear regressionPhase extraction

In book

Communications in Computer and Information Science
Vol. 615: Databases and Information Systems - 12th International Baltic Conference. , Springer, 2016.
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