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Development of finger-motion capturing device based on optical linear encoder.

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  • 1Robotics Research Centre, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore.

Journal of Rehabilitation Research and Development
|February 18, 2011
PubMed
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A new wearable motion capture device, the SmartGlove, utilizes a novel optical linear encoder (OLE) for accurate finger joint tracking. User studies confirm its high repeatability and reliability compared to other data gloves.

Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Human-Computer Interaction

Background:

  • Accurate multifinger motion capture is crucial for various applications, including rehabilitation and virtual reality.
  • Existing data gloves often face limitations in accuracy, comfort, or power consumption.

Purpose of the Study:

  • To design and validate a novel wearable glove-based multifinger-motion capture device (SmartGlove).
  • To develop and integrate a new compact, lightweight, and low-power optical linear encoder (OLE) for precise finger joint angle measurement.

Main Methods:

  • Development of a custom optical linear encoder (OLE) with characterization tests for linearity and accuracy.
  • Construction of the first SmartGlove prototype using 10 OLEs to capture 14 finger joint motions via a multipoint-sensing method.

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  • Evaluation of the SmartGlove through a user study using a standardized protocol, comparing its performance against four other data gloves.

    • Main Results:

    • The developed OLE demonstrated good linearity and accuracy in digital output.
    • The SmartGlove prototype successfully captured multifinger motion, tracking 14 finger joints.
    • User study results indicated high repeatability and reliability for the SmartGlove in both gripped and flat-hand positions.

    Conclusions:

    • The SmartGlove, incorporating a novel OLE, offers a reliable and accurate solution for multifinger motion capture.
    • The device shows superior performance in repeatability and reliability compared to existing data gloves.
    • This technology has potential applications in fields requiring precise hand movement tracking.