Cybernetics of the mind: learning individual's perceptions autonomously

Plamen Parvanov Angelov, Xiaowei Gu, Jose Iglesias, Agapito Ledezma, Araceli Sanchis, Oscar Sipele, Ramin Ramezani

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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.
Original languageEnglish
Pages (from-to)6-17
JournalIEEE Systems, Man, and Cybernetics Magazine
Volume3
Issue number2
Early online date17 Apr 2017
DOIs
Publication statusPublished - 18 Apr 2017
Externally publishedYes

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