Author:
Mieko Tanaka-Yamawaki
Affiliation:
Tottori University, Japan
Keyword(s):
Human Random Generation, HURG, pattern recognition, randomness, mobile phone keyboards, MPK,
Inverse-Ten-Key.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Symbolic Systems
Abstract:
Human Random Generation (HURG) is a psychological test meant to detect the degree of mental fatigue, or the level of concentration of individual subject, by testing the flexibility of thinking, without relying on any equipment(Wagenaar, 1977). In early days, HURG was practiced in clinical psychology in order to detect advanced level of schizophrenia. Later, the development of powerful computers made us possible to detect subtle irregularity hidden in HURG taken from normal subjects. We have been studying the possibility of utilizing HURG for self-detection of dementia at early stage, by using various information theoretical techniques over several years including the pattern classification by means of hidden Markov model (HMM), correlation dimension frequently used to identify chaotic time series, and selection of index suitable to characterize short sequences. In this paper, we report our recent progress in developing a novel method of HURG by using the pattern recognition and the r
andomness measured in the data taken from the Inverse-Ten-Key on the mobile phone keyboards (MPK).
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