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Paper Abstract and Keywords
Presentation 2020-05-29 10:25
FPGA-based human motion estimation based on amalgamated data from multiple sensors
Xin Du, Yutaka Shinkai, Mizuki Itoh, Yoshiki Yamaguchi (Tsukuba Univ.) RECONF2020-12
Abstract (in Japanese) (See Japanese page) 
(in English) This study proposes an FPGA-based system for identifying and estimating human motion by detecting data from sensors in different locations on the human body. A sensor placed on the person captures the acceleration in three directions as the person moves, and the system recognized the person’s action by the variation in these accelerations. A neural network named Self-Organizing map (SOM) is applied to clustering and prediction of multiple sensor data. Finally, this system will be implemented on FPGA, considering that the characteristics of FPGA which include high parallelism and low latency can provide accelerated support for neural network operations. The system in this research is based on Xilinx Spartan-6 FPGA and accelerometers used in this study is DSP wireless 9-axis sensor provided by SPORTS SENSING Co., LTD.
Keyword (in Japanese) (See Japanese page) 
(in English) Self Organizing Map (SOM) / Human motion classification / Accelerometer / Sensor data integration / FPGA / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 36, RECONF2020-12, pp. 65-70, May 2020.
Paper # RECONF2020-12 
Date of Issue 2020-05-21 (RECONF) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF RECONF2020-12

Conference Information
Committee RECONF  
Conference Date 2020-05-28 - 2020-05-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Reconfigurable system, etc. 
Paper Information
Registration To RECONF 
Conference Code 2020-05-RECONF 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) FPGA-based human motion estimation based on amalgamated data from multiple sensors 
Sub Title (in English)  
Keyword(1) Self Organizing Map (SOM)  
Keyword(2) Human motion classification  
Keyword(3) Accelerometer  
Keyword(4) Sensor data integration  
Keyword(5) FPGA  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Xin Du  
1st Author's Affiliation Tsukuba University (Tsukuba Univ.)
2nd Author's Name Yutaka Shinkai  
2nd Author's Affiliation Tsukuba University (Tsukuba Univ.)
3rd Author's Name Mizuki Itoh  
3rd Author's Affiliation Tsukuba University (Tsukuba Univ.)
4th Author's Name Yoshiki Yamaguchi  
4th Author's Affiliation Tsukuba University (Tsukuba Univ.)
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Speaker Author-1 
Date Time 2020-05-29 10:25:00 
Presentation Time 25 minutes 
Registration for RECONF 
Paper # RECONF2020-12 
Volume (vol) vol.120 
Number (no) no.36 
Page pp.65-70 
#Pages 6 
Date of Issue 2020-05-21 (RECONF) 

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