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Cybernetics of the mind: learning individual's perceptions autonomously

Research output: Contribution to journalJournal article

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<mark>Journal publication date</mark>04/2017
<mark>Journal</mark>IEEE Systems, Man, and Cybernetics Magazine
Issue number2
Volume3
Number of pages12
Pages (from-to)6-17
Publication statusPublished
Early online date17/04/17
Original languageEnglish

Abstract

In this article, we describe an approach to computational modeling and autonomous learning of the perception of sensory inputs by individuals. A hierarchical process of summarization of heterogeneous raw data is proposed. At the lower level of the hierarchy, the raw data autonomously form semantically meaningful concepts. Instead of clustering based on visual or audio similarity, the concepts are formed at the second level of the hierarchy based on observed physiological variables (PVs) such as heart rate and skin conductance and are mapped to the emotional state of the individual. Wearable sensors were used in the experiments.

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©2017 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.