Evaluation of writing motion using principal component analysis and scaling analysis

被引:0
|
作者
Hayashi, Kotaro [1 ]
Uchida, Masafumi [1 ]
机构
[1] Univ Electro Commun, Grad Sch Informat & Engn, 1-5-1 Chofugaoka, Tokyo, Japan
关键词
Handwriting task; Fluctuation; One-over-f fluctuation; White noise; Detrended fluctuation analysis; Principal component analysis;
D O I
10.1007/s10015-022-00836-w
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
The control of voluntary movements is a dual structure consisting of cognitive and physical controls; cognitive control, unlike physical control requires attentional resources. Various voluntary movements can be performed by combining cognitive and physical controls. Body movements depending on attentional resources are performed using cognitive control; these movements fluctuate with white noise and their fluctuations gradually change to one-over-f fluctuation as the dependence on attentional resources decreases. Characters are handwriting processes in voluntary movement. This study focused on the relationship between a repetitive handwriting process and attentional resources allocated to it. The attention resources allocated to handwriting processes depend on how challenging the task is. Moreover, the difficulty of a handwriting task is determined by the complexity of the shape of the handwritten characters, and the stroke counts are one indicator of this. Therefore, we focused on three Chinese kanji characters with different stroke counts. Attentional resources can be identified by tapping movements concurrently with writing movements and comparing the result. An experiment was conducted for 6 days for each of the three Chinese kanji characters, with 25 subjects who were familiar with the Chinese kanji character. We investigated fluctuations in the six temporal handwriting elements defined within each Chinese kanji character handwriting process. In the analysis, six-dimensional temporal handwriting elements were reduced to three dimensions using principal component analysis. Furthermore, detrended fluctuation analysis was applied to the three-dimensional principal components. In this study, we examine the effectiveness of principal component analysis for the analysis of multidimensional data. Furthermore, we discussed the relationship between handwriting task difficulties and temporal handwriting elements using local scaling indices based on detrended fluctuation analysis.
引用
收藏
页码:425 / 434
页数:10
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