Feature Extraction based on Touch Interaction Data in Virtual Reality-based IADL for Characterization of Mild Cognitive Impairment

Yuki Kubota, Takehiko Yamaguchi, Takuya Maeta, Yosuke Okada, Yoshihito Miura, Niken Prasasti Martono, Hayato Ohwada, Giovannetti Tania

Abstract

The aim of this study was to explore the feature pattern of Mild Cognitive Impairment (MCI) in Virtual Reality based Instrumental Activities of Daily Living (VR-IADL) which runs on a tablet PC as well as requires participants a touch interaction to complete the task. Twelve participants (MCI: 4, history of MCI: 2, healthy elderly: 6) were recruited from the region of Philadelphia in USA to perform a VR-IADL task. We found that Non Touch Time (NTT) which is time interval during not touching screen on tablet was longer than that of MCI patients as well as healthy older adults with having history of MCI. Several types of feature patterns were extracted from the NTT such as … Based on the feature pattern, Support Vector Machine (SVM) was performed to calculate the accuracy of the feature patter for characterization of MCI. As the result, the identification rate was 75%.

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Paper Citation


in Harvard Style

Kubota Y., Yamaguchi T., Maeta T., Okada Y., Miura Y., Martono N., Ohwada H. and Tania G. (2017). Feature Extraction based on Touch Interaction Data in Virtual Reality-based IADL for Characterization of Mild Cognitive Impairment . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017) ISBN 978-989-758-229-5, pages 152-157. DOI: 10.5220/0006265201520157


in Bibtex Style

@conference{hucapp17,
author={Yuki Kubota and Takehiko Yamaguchi and Takuya Maeta and Yosuke Okada and Yoshihito Miura and Niken Prasasti Martono and Hayato Ohwada and Giovannetti Tania},
title={Feature Extraction based on Touch Interaction Data in Virtual Reality-based IADL for Characterization of Mild Cognitive Impairment},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017)},
year={2017},
pages={152-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006265201520157},
isbn={978-989-758-229-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: HUCAPP, (VISIGRAPP 2017)
TI - Feature Extraction based on Touch Interaction Data in Virtual Reality-based IADL for Characterization of Mild Cognitive Impairment
SN - 978-989-758-229-5
AU - Kubota Y.
AU - Yamaguchi T.
AU - Maeta T.
AU - Okada Y.
AU - Miura Y.
AU - Martono N.
AU - Ohwada H.
AU - Tania G.
PY - 2017
SP - 152
EP - 157
DO - 10.5220/0006265201520157