casa 18(13): e4

Research Article

Visible Position Estimation in Whole Wrist Circumference Device towards Forearm Pose-aware Display

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  • @ARTICLE{10.4108/eai.14-3-2018.154341,
        author={Yuki Tanida and Kaori Fujinami},
        title={Visible Position Estimation in Whole Wrist Circumference Device towards Forearm Pose-aware Display},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={4},
        number={13},
        publisher={EAI},
        journal_a={CASA},
        year={2018},
        month={3},
        keywords={wearable computing; flexible display; wrist-worn device; accelerometer; notification; LED; machine learning},
        doi={10.4108/eai.14-3-2018.154341}
    }
    
  • Yuki Tanida
    Kaori Fujinami
    Year: 2018
    Visible Position Estimation in Whole Wrist Circumference Device towards Forearm Pose-aware Display
    CASA
    EAI
    DOI: 10.4108/eai.14-3-2018.154341
Yuki Tanida1, Kaori Fujinami2,*
  • 1: Department of Industrial Technology and Innovation, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan
  • 2: Department of Computer and Information Sciences, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan
*Contact email: fujinami@cc.tuat.ac.jp

Abstract

Smart watches allow instant access to information; however, the visual notification is not always reachable depending on the forearm posture. Flexible and curved display technologies can enable full-wrist circumference displays that show information at the most visible positions using pose awareness. A prototype device is implemented with 10 LEDs and 10 accelerometers around the wrist. The most visible LED is estimated using a machine learning technique. The main idea is to utilize direct relationship between the raw acceleration signals and the position of the most visible LED, rather than assigning the position by particular classes of activities or forward-kinematic model-based estimation. Also, sensor reduction is attempted by introducing new features. A user study showed that the system allowed 89.9 % of the system’s judgment to fit with the gap of 1 LED (18 mm) from the user’s expectations. The rotation-sensitive features proved to be informative, and a single sensor placed on the inside of the wrist achieved a performance level on par (F-measure 0.681) with the performance when all (10) sensors are used.