Publication: Can we accurately measure axial segment coordination during turning using inertial measurement units (IMUs)?
Issued Date
2020-05-01
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14248220
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2-s2.0-85084276426
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Mahidol University
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SCOPUS
Bibliographic Citation
Sensors (Switzerland). Vol.20, No.9 (2020)
Suggested Citation
Fuengfa Khobkhun, Mark A. Hollands, Jim Richards, Amornpan Ajjimaporn Can we accurately measure axial segment coordination during turning using inertial measurement units (IMUs)?. Sensors (Switzerland). Vol.20, No.9 (2020). doi:10.3390/s20092518 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/56118
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Title
Can we accurately measure axial segment coordination during turning using inertial measurement units (IMUs)?
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Abstract
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Camera-based 3D motion analysis systems are considered to be the gold standard for movement analysis. However, using such equipment in a clinical setting is prohibitive due to the expense and time-consuming nature of data collection and analysis. Therefore, Inertial Measurement Units (IMUs) have been suggested as an alternative to measure movement in clinical settings. One area which is both important and challenging is the assessment of turning kinematics in individuals with movement disorders. This study aimed to validate the use of IMUs in the measurement of turning kinematics in healthy adults compared to a camera-based 3D motion analysis system. Data were collected from twelve participants using a Vicon motion analysis system which were compared with data from four IMUs placed on the forehead, middle thorax, and feet in order to determine accuracy and reliability. The results demonstrated that the IMU sensors produced reliable kinematic measures and showed excellent reliability (ICCs 0.80–0.98) and no significant differences were seen in paired t-tests in all parameters when comparing the two systems. This suggests that the IMU sensors provide a viable alternative to camera-based motion capture that could be used in isolation to gather data from individuals with movement disorders in clinical settings and real-life situations.