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 |
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| Hauptverfasser: | , , , |
| 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. |
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| 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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| 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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