Authors:
Yuki Kubota
1
;
Takehiko Yamaguchi
2
;
Takuya Maeta
1
;
Yosuke Okada
2
;
Yoshihito Miura
2
;
Niken Prasasti Martono
2
;
Hayato Ohwada
2
and
Giovannetti Tania
3
Affiliations:
1
Graduated of Tokyo University of Science, Japan
;
2
Tokyo University of Science, Japan
;
3
Temple University, United States
Keyword(s):
Dementia, MCI, Screening, VR-IADK, Characterization.
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%.
