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Related Experiment Video

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Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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Hidden marker position estimation during sit-to-stand with walker.

Sang Ho Yoon1, Hong Gul Jun, Byung Ju Dan

  • 1Convergence Laboratory, LG Electronics Inc., 221, Yanjae-Dong, Seoul 137-130, Korea. sangho7.yoon@lge.com

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
Summary

This study introduces a method to restore lost motion capture marker data during sit-to-stand analysis using the Smart Mobile Walker. This enables accurate biomechanical evaluation of assistive device use.

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Area of Science:

  • Biomechanics
  • Robotics
  • Human Movement Analysis

Background:

  • Motion capture for sit-to-stand (STS) tasks is challenging with assistive devices due to marker obstruction.
  • The Smart Mobile Walker (SMW) is a robotic assistive device requiring motion analysis.

Purpose of the Study:

  • To develop and validate a method for estimating lost marker positions during STS with the SMW.
  • To enable comprehensive biomechanical evaluation of STS using the SMW.

Main Methods:

  • Utilized a link-segment and regression method to estimate occluded lower limb marker positions.
  • Applied a novel technique to restore marker data lost during the STS task.
  • Validated marker position estimation accuracy against normal STS data from over 30 clinical trials.

Main Results:

  • Successfully restored occluded marker positions during STS with the SMW.
  • Enabled biomechanical evaluation of STS movement with the assistive device.
  • Demonstrated accuracy of the marker estimation method through clinical trial data.

Conclusions:

  • The developed method effectively restores lost marker data for motion capture during STS with assistive devices.
  • This facilitates accurate biomechanical analysis of human-robot interaction in mobility tasks.
  • Further research is recommended to refine the link-segment and regression techniques.