An Analysis of Motion Transition in Subtle Errors using Inductive Logic Programming: A Case Study in Approaches to Mild Cognitive Impairment

This article seeks to utilize the data collected from virtual reality (VR)-based software and a leap-motion device used for learning of subtle errors in mild cognitive impairment (MCI) cases to enable early detection of MCI by analyzing the classification rules for errors (action slips) based on fin...

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Veröffentlicht in:International journal of software science and computational intelligence Jg. 10; H. 1; S. 27 - 37
Hauptverfasser: Ohwada, Hayato, Martono, Niken Prasasti, Abe, Keisuke, Yamaguchi, Takehiko
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hershey IGI Global 01.01.2018
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ISSN:1942-9045, 1942-9037
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Abstract This article seeks to utilize the data collected from virtual reality (VR)-based software and a leap-motion device used for learning of subtle errors in mild cognitive impairment (MCI) cases to enable early detection of MCI by analyzing the classification rules for errors (action slips) based on finger-action transitions when performing instrumental activities of daily living (IADL). Finger motion was recorded as a time-series database. An induction technique known as Inductive-Logic Programming (ILP), which uses logical and clausal language to represent the training data, was then used to discover a concise classification rule using logical programming. The content within this article was able to generate rules on how action transitions of the finger in the experiments were related to the pattern of micro-errors that indicate the difference of error regarding the length of the no-motion state of the finger.
AbstractList This article seeks to utilize the data collected from virtual reality (VR)-based software and a leap-motion device used for learning of subtle errors in mild cognitive impairment (MCI) cases to enable early detection of MCI by analyzing the classification rules for errors (action slips) based on finger-action transitions when performing instrumental activities of daily living (IADL). Finger motion was recorded as a time-series database. An induction technique known as Inductive-Logic Programming (ILP), which uses logical and clausal language to represent the training data, was then used to discover a concise classification rule using logical programming. The content within this article was able to generate rules on how action transitions of the finger in the experiments were related to the pattern of micro-errors that indicate the difference of error regarding the length of the no-motion state of the finger.
Audience Academic
Author Martono, Niken Prasasti
Ohwada, Hayato
Yamaguchi, Takehiko
Abe, Keisuke
AuthorAffiliation Tokyo University of Science, Noda, Japan
Department of Industrial Administration, Tokyo University of Science, Noda, Japan
Tokyo University of Science, Suwa, Japan
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Cites_doi 10.1212/01.wnl.0000252358.03285.9d
10.1080/09602011.2015.1094394
10.3384/diss.diva-115349
10.4018/IJSSCI.2016100102
10.1080/09602010244000084
10.4135/9788132107910.n7
10.1080/13854046.2013.852624
10.1111/j.1365-2796.2004.01380.x
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Copyright COPYRIGHT 2018 IGI Global
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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SubjectTerms Activities of daily living
Case studies
Classification
Cognitive ability
Dementia
Disease
Errors
Human error
Impairment
Logic programming
Machine learning
Memory
Older people
Program errors
Science
Software
Virtual reality
Title An Analysis of Motion Transition in Subtle Errors using Inductive Logic Programming: A Case Study in Approaches to Mild Cognitive Impairment
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