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指輪型無線検知装置による連続指ジェスチャのリアルタイム分割、認識と応用の研究

Research Project

Project/Area Number 13J09319
Research Category

Grant-in-Aid for JSPS Fellows

Allocation TypeSingle-year Grants
Section国内
Research Field Computer system/Network
Research InstitutionThe University of Aizu

Principal Investigator

周 頴慧  会津大学, コンピュータ理工学研究科, 特別研究員(DC2)

Project Period (FY) 2013-04-01 – 2015-03-31
Project Status Completed (Fiscal Year 2014)
Budget Amount *help
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2014: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2013: ¥900,000 (Direct Cost: ¥900,000)
Keywordswearable computing / gesture segmentation / gesture recognition / daily activity detection / adaptive threshold / hidden Markov model / sequence alignment / activity detection / weighted sequence alignment
Outline of Annual Research Achievements

Wearable computing is an important technology in health care. We developed a natural and light weight finger-worn interface to identify user gestures and activities for long-term life support.Three key issues are solved as follows.
Segmentation of gesture sequence is a precondition in wearable computing. We proposed an adaptive threshold-based method based on Bayes Decision Theory and designed an adaptive mechanism to segment short-duration, ambiguous, and individually different gestures. The method can obtain high segmentation precision/recall and user-dependent adaptability with low computation complexity.
Recognition is the resolution of wearable computing. We proposed a pre-classification HMM method that can reduce recognition complexity by dividing gesture vocabularies into groups, maintain or even improve recognition accuracy by the adaptive adjustment of HMMs for different groups.
Application is the final goal of wearable computing. We employed only one finger-worn device to detect ten daily activities. To reflect realistic life aspects, a weight sequence alignment approach is proposed to analyze the detected activity sequences and attributes of each activity. The method can provide more detailed and realistic information of users' living for discover of potential health problem.
In summary, our finger-worn interface can detect finger/hand gestures and identify users’ daily activities. It has many potential applications like appliance control and health monitoring, which is especially useful for health care of elderly person in the aging society.

Research Progress Status

26年度が最終年度であるため、記入しない。

Strategy for Future Research Activity

26年度が最終年度であるため、記入しない。

Report

(2 results)
  • 2014 Annual Research Report
  • 2013 Annual Research Report
  • Research Products

    (6 results)

All 2015 2014 2013

All Journal Article (3 results) (of which Peer Reviewed: 3 results,  Open Access: 1 results,  Acknowledgement Compliant: 2 results) Presentation (3 results)

  • [Journal Article] Towards unobtrusive detection and realistic attribute analysis of daily activity sequences using a finger-worn device2015

    • Author(s)
      Y. Zhou, Z. Cheng, L. Jing, T. Hasegawa
    • Journal Title

      Applied Intelligence

      Volume: - Issue: 2 Pages: 386-396

    • DOI

      10.1007/s10489-015-0649-y

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed / Acknowledgement Compliant
  • [Journal Article] Pre-classification Based Hidden Markov Model for Quick and Accurate Gesture Recognition Using a Finger-worn Device2014

    • Author(s)
      Y. Zhou, Z. Cheng, L. Jing, J. Wang, T. Huang
    • Journal Title

      Applied Intelligence

      Volume: 40 Issue: 4 Pages: 613-622

    • DOI

      10.1007/s10489-013-0492-y

    • Related Report
      2014 Annual Research Report 2013 Annual Research Report
    • Peer Reviewed / Open Access / Acknowledgement Compliant
  • [Journal Article] Threshold selection and adjustment for online segmentation of one-stroke finger gestures using single tri-axial accelerometer2014

    • Author(s)
      Y. Zhou, Z. Cheng, L. Jing
    • Journal Title

      Multimedia Tools and Applications

      Volume: - Issue: 21 Pages: 9387-9406

    • DOI

      10.1007/s11042-014-2111-2

    • Related Report
      2014 Annual Research Report
    • Peer Reviewed
  • [Presentation] A System of Life Support based on Behavior Detection and Social Networking Technology2014

    • Author(s)
      Y. Zhou, Y. Asano, Z. Cheng, and L. Jing
    • Organizer
      2014 International Symposium on Cloud and Services Computing
    • Place of Presentation
      Park Plaza Beijing Science Park (Beijing, China)
    • Year and Date
      2014-09-01 – 2014-09-03
    • Related Report
      2014 Annual Research Report
  • [Presentation] Adaptive Template Adjustment for Personalized Gesture Recognition Based on a Finger-worn Device2013

    • Author(s)
      Y. Zhou, D. Saito, L. Jing
    • Organizer
      2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing
    • Place of Presentation
      会津大学
    • Related Report
      2013 Annual Research Report
  • [Presentation] Recognition of Continuous Gestures by A Finger-worn device2013

    • Author(s)
      Y. Zhou, D. Saito, L. Jing
    • Organizer
      2013 Tohoku-section Joint Convention of Institutes of Electrical and Information Engineers
    • Place of Presentation
      会津大学
    • Related Report
      2013 Annual Research Report

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Published: 2014-01-29   Modified: 2024-03-26  

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