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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Vydáno v:International journal of software science and computational intelligence Ročník 10; číslo 1; s. 27 - 37
Hlavní autoři: Ohwada, Hayato, Martono, Niken Prasasti, Abe, Keisuke, Yamaguchi, Takehiko
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hershey IGI Global 01.01.2018
Témata:
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
Japan
ISSN:1942-9045, 1942-9037
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Shrnutí: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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ISSN:1942-9045
1942-9037
DOI:10.4018/IJSSCI.2018010103