지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이 논문의 연구 히스토리 (5)
2022
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This paper deals with relative position estimation using a Kalman filter (KF) based on inertial sensors that have been widely used in various biomechanics-related outdoor applications. In previous studies, the relative position is determined using relative orientationand predetermined segment-to-joint (S2J) vectors, which are assumed to be constant. However, because body segments are influenced by soft tissue artifacts (STAs), including the deformation and sliding of the skin over the underlying bone structures, they are not constant,resulting in significant errors during relative position estimation. In this study, relative position estimation was performed using a KF, where the S2J vectors were adopted as time-varying states. The joint constraint and the variations of the S2J vectors were usedto develop a measurement model of the proposed KF. Accordingly, the covariance matrix corresponding to the variations of the S2J vectors continuously changed within the ranges of the STA-causing flexion angles. The experimental results of the knee flexion testsshowed that the proposed KF decreased the estimation errors in the longitudinal and lateral directions by 8.86 and 17.89 mm, respectively, compared with a conventional approach based on the application of constant S2J vectors.
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참고문헌 (22)
참고문헌 신청
G. Pons-Moll / 2010 / Multisensor-fusion for 3D full-body human motion capture / Proc. of IEEE Conf. on Comput. Vis. Pattern Recognit :663~670
M. Kok / 2014 / An optimizationbased approach to human body motion capture using inertial sensors / Proc. of 19th World Congr. Int. Fed. Autom. Control :79~85
A. Atrsaei / 2018 / Human arm motion tracking by inertial/magnetic sensors using unscented Kalman filter and relative motion constraint / J. Intell. Robot. Syst 90:161~170
G. Cooper / 2009 / Inertial sensor-based knee flexion/extension angle estimation / J. Biomech. 42(16):2678~2685
B. Fasel / 2018 / Joint inertial sensor orientation drift reduction for highly dynamic movements / IEEE J. Biomed. Health Inform 22(1):77~86
M. Kok / 2014 / An optimizationbased approach to human body motion capture using inertial sensors / Proc. of 19th World Congr. Int. Fed. Autom. Control :79~85
A. Atrsaei / 2018 / Human arm motion tracking by inertial/magnetic sensors using unscented Kalman filter and relative motion constraint / J. Intell. Robot. Syst 90:161~170
G. Cooper / 2009 / Inertial sensor-based knee flexion/extension angle estimation / J. Biomech. 42(16):2678~2685
B. Fasel / 2018 / Joint inertial sensor orientation drift reduction for highly dynamic movements / IEEE J. Biomed. Health Inform 22(1):77~86
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