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"Motion capture"

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Reliability Verification of Shoulder Joint Range of Motion Measurement Using OpenCV and Motion Capture
조근식 , 조영준 , 최인식 , 송치연 , 염성환 , 장웅기 , 박희원 , 김현욱 , 하석진 , 김병희 , 박용재
J. Korean Soc. Precis. Eng. 2023;40(7):511-518.
Published online July 1, 2023
DOI: https://doi.org/10.7736/JKSPE.023.046
As the population ages, the concept of active seniors has been emerging recently. Among various body parts that are cared for by an active elderly, the shoulder has a unique exercise structure. Therefore, the incidence of shoulder injuries might be high. In the case of a shoulder disease, the method of measuring the movement angle of the shoulder is mainly used. To measure the movement angle of a shoulder accurately, a goniometer is used. In addition, we suggested self-diagnosis, believing that if shoulder disease could be detected early through self-diagnosis, rapid treatment will be possible. This paper measured and compared shoulder angles with the goniometer, OpenCV, and motion capture systems to determine measurement errors between them. Through experimental results of this paper, the possibility of self-diagnosis with precise measurement of the movement angle of a shoulder oneself with a goniometer was confirmed even if the expert could not measure the shoulder angle.
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IMU based Walking Position Tracking using Kinematic Model of Lower Body and Walking Cycle Analysis
Kee Wook Song, Young Eun Song, Hoeryong Jung
J. Korean Soc. Precis. Eng. 2018;35(10):965-972.
Published online October 1, 2018
DOI: https://doi.org/10.7736/KSPE.2018.35.10.965
This paper proposes a walking position tracking method using inertial measurement unit (IMU) based on kinematic model of human body and walking cycle analysis. A kinematic model of lower body consisting of 9 coordinate frames and 7 links is used to estimate walking trajectory of the body based on rotation angles of the lower body measured by IMU. In this method, the position of left or right end frame of the lower body which is in contact with the ground is first identified and set as the reference position. The position of the base frame attached on the center of pelvis is then computed using the kinematic model and the reference position. One can switch the reference position with the position of the other end frame at the moment of heel strike. The proposed position tracking method was experimentally validated. Experimental result showed that position tracking errors were within 1.4% of walking distance for straight walking and 2.2% for circular walking.

Citations

Citations to this article as recorded by  Crossref logo
  • Evaluation of Ergonomic Performance of Medical Smart Insoles
    Jae-Hoon Yi, Jin-Wook Lee, Dong-Kwon Seo
    Physical Therapy Rehabilitation Science.2022; 11(2): 215.     CrossRef
  • Detection of Human Gait Phases Using Textile Pressure Sensors: A Low Cost and Pervasive Approach
    Matko Milovic, Gonzalo Farías, Sebastián Fingerhuth, Francisco Pizarro, Gabriel Hermosilla, Daniel Yunge
    Sensors.2022; 22(8): 2825.     CrossRef
  • Inertial Sensor-Based Relative Position Estimation between Upper Body Segments Considering Non-Rigidity of Human Bodies
    Chang June Lee, Jung Keun Lee
    Journal of the Korean Society for Precision Engineering.2021; 38(3): 215.     CrossRef
  • Gait Analysis Accuracy Difference with Different Dimensions of Flexible Capacitance Sensors
    DongWoo Nam, Bummo Ahn
    Sensors.2021; 21(16): 5299.     CrossRef
  • Development of Wearable Sensing Suit for Monitoring Wrist Joint Motions and Deep Neural Network-based Calibration Method
    Junhwi Cho, Hyunkyu Park, Jung Kim
    Journal of the Korean Society for Precision Engineering.2020; 37(10): 765.     CrossRef
  • Kinematic Constraint-Projected Kalman Filter to Minimize Yaw Estimation Errors Induced by Magnetic Distortions
    Tae Hyeong Jeon, Jung Keun Lee
    Journal of the Korean Society for Precision Engineering.2019; 36(7): 659.     CrossRef
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