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Paper Abstract and Keywords
Presentation 2023-06-16 16:15
Proposing a Feature-Analysis Method of Finger-Movement Data for Predicting Cognitive Function of Elderly People
Hayato Seiichi, Sinan Chen, Atsuko Hayashi, Masahide Nakamura (Kobe Univ.) WIT2023-6
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, a growing body of research has suggested a relationship between cognitive function and manual dexterity. However, studies on all aspects of human fingertip movements have been limited, and analysis methods still need to be well-established. Our research group is developing a finger motion measurement system that combines image recognition and touch panel manipulation. Therefore, the purpose of this study is to utilize the finger motion data extracted using our developed system and propose an analysis method for assessing manual dexterity. Our key idea is to focus on irregularly sampled finger motion time-series data and analyze it using a state-space model. The proposed method follows steps: (Step 1) Data loading and organization. (Step 2) Coordinate data transformation. (Step 3) Individual comparison of data features. In a case study, we extract data measured according to two types of tapping tasks (i.e., normal task and n-back task). We provide analysis examples of four parameters: reaction time and speed of finger motion, the difference in distance, and angle. We also discuss the findings, highlighting the differences from related studies and identifying areas for improvement in our method. It expects to establish new indicators for manual dexterity, enabling the early detection of signs of cognitive decline in older adults.
Keyword (in Japanese) (See Japanese page) 
(in English) Cognitive function prediction / Finger movements / Time-series data / State-space model / Feature analysis / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 81, WIT2023-6, pp. 30-35, June 2023.
Paper # WIT2023-6 
Date of Issue 2023-06-09 (WIT) 
ISSN Online edition: ISSN 2432-6380
Copyright
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee WIT  
Conference Date 2023-06-16 - 2023-06-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To WIT 
Conference Code 2023-06-WIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposing a Feature-Analysis Method of Finger-Movement Data for Predicting Cognitive Function of Elderly People 
Sub Title (in English)  
Keyword(1) Cognitive function prediction  
Keyword(2) Finger movements  
Keyword(3) Time-series data  
Keyword(4) State-space model  
Keyword(5) Feature analysis  
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1st Author's Name Hayato Seiichi  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Sinan Chen  
2nd Author's Affiliation Kobe University (Kobe Univ.)
3rd Author's Name Atsuko Hayashi  
3rd Author's Affiliation Kobe University (Kobe Univ.)
4th Author's Name Masahide Nakamura  
4th Author's Affiliation Kobe University (Kobe Univ.)
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Speaker Author-1 
Date Time 2023-06-16 16:15:00 
Presentation Time 25 minutes 
Registration for WIT 
Paper # WIT2023-6 
Volume (vol) vol.123 
Number (no) no.81 
Page pp.30-35 
#Pages
Date of Issue 2023-06-09 (WIT) 


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