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Poster

VR based Collaborative Errorless Learning System Using Humanoid Avatar for People with Alzheimer’s disease

Abstract : Everyday action impairment is one of the diagnostic criteria of Alzheimer’s disease and is associated with many serious consequences, including loss of functional autonomy and independence. It has been shown that the (re)learning of everyday activities is possible in Alzheimer’s disease by using errorless learning approaches. The purpose of this study is to propose a newly revised Virtual Kitchen system that allows training of everyday activities to integrate a new approach of errorless learning (EL) framework using collaborative learning with a virtual agent. In this paper, we describe a concept of the proposed framework, as well as explore user’s attention change to analyse eye tracking data during a training task in order to review the effectiveness of the proposed EL framework.
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https://hal.univ-angers.fr/hal-02525526
Contributeur : Okina Université d'Angers <>
Soumis le : mardi 31 mars 2020 - 03:07:13
Dernière modification le : lundi 15 juin 2020 - 18:32:09

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Takehiko Yamaguchi, Yuta Yamagami, Toshihiko Sato, Hibiki Fujino, Testsuya Harada, et al.. VR based Collaborative Errorless Learning System Using Humanoid Avatar for People with Alzheimer’s disease. 10 th International Conference on Computer Graphics Theory and Applications (GRAPP’15), 2015, Berlin, Germany. SciTePress, pp.462-469, 2015, ⟨10.5220/0005313904620469⟩. ⟨hal-02525526⟩

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