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Detection and Quantification of Screw-Home Movement Using Nine-Axis Inertial Sensors
J Kor Phys Ther 2019;31(6):333-338
Published online December 30, 2019;
© 2019 The Korea Society of Physical Therapy.

Jeong Woo Jeon, Dong Yeop Lee, Jae Ho Yu, Jin Seop Kim, Jiheon Hong

Department of Physical Therapy, College of Health Science, Sun Moon University, Asan, Korea
Jiheon Hong E-mail
Received September 4, 2019; Revised October 10, 2019; Accepted October 10, 2019.
This is an Open Access article distribute under the terms of the Creative Commons Attribution Non-commercial License (Http:// which permits unrestricted non-commercial use, distribution,and reproduction in any medium, provided the original work is properly cited.
Purpose: Although previous studies on the screw-home movement (SHM) for autopsy specimen and walking of living persons conducted, the possibility of acquiring SHM based on inertial measurement units received little attention. This study aimed to investigate the possibility of measuring SHM for the non-weighted bearing using a micro-electro-mechanical system-based wearable motion capture system (MEMSS).
Methods: MEMSS and camera-based motion analysis systems were used to obtain kinematic data of the knee joint. The knee joint moved from the flexion position to a fully extended position and then back to the start point. The coefficient of multiple correlation and the difference in the range of motion were used to assess the waveform similarity in the movement measured by two measurement systems.
Results: The waveform similarity in the sagittal plane was excellent and the in the transverse plane was good. Significant differences were found in the sagittal plane between the two systems (p<0.05). However, there was no significant difference in the transverse plane between the two systems (p>0.05).
Conclusion: The SHM during the passive motion without muscle contraction in the non-weighted bearing appeared in the entire range. We thought that the MEMSS could be easily applied to the acquisition of biomechanical data on the knee related to physical therapy.
Keywords : Screw-home movement, Biomechanics, Inertial sensor, Micro-Electro-Mechanical System

December 2019, 31 (6)
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