TY - JOUR
T1 - Cybernetics of the mind
T2 - learning individual's perceptions autonomously
AU - Angelov, Plamen Parvanov
AU - Gu, Xiaowei
AU - Iglesias, Jose
AU - Ledezma, Agapito
AU - Sanchis, Araceli
AU - Sipele, Oscar
AU - Ramezani, Ramin
PY - 2017/4/18
Y1 - 2017/4/18
N2 - 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.
AB - 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.
U2 - 10.1109/MSMC.2017.2664478
DO - 10.1109/MSMC.2017.2664478
M3 - Article
SN - 2380-1298
VL - 3
SP - 6
EP - 17
JO - IEEE Systems, Man, and Cybernetics Magazine
JF - IEEE Systems, Man, and Cybernetics Magazine
IS - 2
ER -