시변 분절-관절 벡터를 통한 상대위치 추정시 변형관련 변수의 선정이 추정 정확도에 미치는 영향
Effects of the Selection of Deformation-related Variables on Accuracy in Relative Position Estimation via Time-varying Segment-to-Joint Vectors
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This study estimates the relative position between body segments using segment orientation and segment-to-joint center (S2J) vectors. In many wearable motion tracking technologies, the S2J vector is treated as a constant based on the assumption that rigid body segments are connected by a mechanical ball joint. However, human body segments are deformable non-rigid bodies, and they are connected via ligaments and tendons; therefore, the S2J vector should be determined as a time-varying vector, instead of a constant. In this regard, our previous study (2021) proposed a method for determining the time-varying S2J vector from the learning dataset using a regression method. Because that method uses a deformation-related variable to consider the deformation of S2J vectors, the optimal variable must be determined in terms of estimation accuracy by motion and segment. In this study, we investigated the effects of deformation-related variables on the estimation accuracy of the relative position. The experimental results showed that the estimation accuracy was the highest when the flexion and adduction angles of the shoulder and the flexion angles of the shoulder and elbow were selected as deformationrelated variables for the sternum-to-upper arm and upper arm-to-forearm, respectively. Furthermore, the case with multiple deformationrelated variables was superior by an average of 2.19 mm compared to the case with a single variable.
Abstract
This study estimates the relative position between body segments using segment orientation and segment-to-joint center (S2J) vectors. In many wearable motion tracking technologies, the S2J vector is treated as a constant based on the assumption that rigid body segments are connected by a mechanical ball joint. However, human body segments are deformable non-rigid bodies, and they are connected via ligaments and tendons; therefore, the S2J vector should be determined as a time-varying vector, instead of a constant. In this regard, our previous study (2021) proposed a method for determining the time-varying S2J vector from the learning dataset using a regression method. Because that method uses a deformation-related variable to consider the deformation of S2J vectors, the optimal variable must be determined in terms of estimation accuracy by motion and segment. In this study, we investigated the effects of deformation-related variables on the estimation accuracy of the relative position. The experimental results showed that the estimation accuracy was the highest when the flexion and adduction angles of the shoulder and the flexion angles of the shoulder and elbow were selected as deformationrelated variables for the sternum-to-upper arm and upper arm-to-forearm, respectively. Furthermore, the case with multiple deformationrelated variables was superior by an average of 2.19 mm compared to the case with a single variable.
참고문헌 (23)
- H. J. Luinge, "Measuring orientation of human body segments using miniature gyroscopes and accelerometers", Med. Biol. Eng. Comput, 43(2), pp.273~282 (2005)
- J. K. Lee, "A fast quaternion-based orientation optimizer via virtual rotation for human motion tracking", IEEE Trans. Biomed. Eng, 56(5), pp.1574~1582 (2008)
- H. G. Kortier, "Hand pose estimation by fusion of inertial and magnetic sensing aided by a permanent magnet", IEEE Trans. Neural Syst. Rehabil. Eng, 23(5), pp.796~806 (2014)
- J. K. Lee, "A parallel attitude-heading Kalman filter without state-augmentation of model-based disturbance components", IEEE Trans. Instrum. Meas, 68(7), pp.2668~2670 (2019)
- Woo-Chang Jung, "Comparison of Drift Reduction Methods for Pedestrian Dead Reckoning Based on a Shoe-Mounted IMU", 센서학회지, 28(6), pp.345~354 (2019), 한국센서학회
- D. Roetenberg, "Ambulatory position and orientation tracking fusing magnetic and inertial sensing", IEEE Trans. Biomed. Eng, 54(5), pp.883~890 (2007)
- M. S. Lee, "Kinematic model-based pedestrian dead reckoning for heading correction and lower body motion tracking", Sensors, 15(11), pp.28129~28153 (2015)
- G. Pons-Moll, "Multisensor-fusion for 3D full-body human motion capture", Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pp.663~670 (2010)
- Y. Zheng, "Pedalvatar : An IMU-based real-time body motion capture system using foot rooted kinematic model", Proc. of 2014 IEEE, 2014, 4130~4135
- M. Kok, "An optimizationbased approach to human body motion capture using inertial sensors", Proc. of 19th World Congr. Int. Federation Autom. Control, pp.79~85 (2014)
- H. Zhou, "Inertial measurements of upper limb motion", Med. Biol. Eng. Comput, 44(6), pp.479~487 (2006)
- A. Atrsaei, "Human arm motion tracking by inertial", magnetic sensors using unscented Kalman filter and relative motion constraint, 2018, pp.90(1), 161~170
- S. G. de Villa, "Adaptive IMU-based calibration of the center of joints for movement analysis : One case study", Proc. of 2020 IEEE Int. Symp. Med. Meas. Appl, pp.1~6 (2020)
- 이창준, "신체 분절의 연조직 변형을 고려한 관성센서신호 기반의 상대위치 추정 칼만필터", 센서학회지, 29(4), pp.237~242 (2020), 한국센서학회
- C. J. Lee, "Wearable IMMU-based relative position estimation between body segments via time-varying segment-to-joint vectors", Sensors, 22(6), pp.2149~ (2022)
- J. Cameron, "A real-time sequential algorithm for human joint localization", Proc. of ACM SIGGRAPH 2005 Posters, pp.107~ (2005)
- T. Seel, "Joint axis and position estimation from inertial measurement data by exploiting kinematic constraints", Proc. of IEEE Int. Conf. Control Appl, pp.45~49 (2012)
- 이정근, "Verification of Two Least-Squares Methods for Estimating Center of Rotation Using Optical Marker Trajectory", 센서학회지, 26(6), pp.371~378 (2017), 한국센서학회[DOI]
- E. Grimpampi, "Metrics for describing soft-tissue artefact and its effect on pose, size, and shape of marker clusters", IEEE Trans. Biomed. Eng, 61(2), pp.362~367 (2013)
- D. L. Benoit, "Surface marker cluster translation, rotation, scaling and deformation : Their contribution to soft tissue artefact and impact on knee joint kinematics", J. Biomech, 48(10), pp.2124~2129 (2015)
- F. D'Isidoro, "Effects of the soft tissue artefact on the hip joint kinematics during unrestricted activities of daily living", J. Biomech, 104, pp.109717(1)~109717(10 (2020)
- 이창준, "인체의 비강체성을 고려한 착용형 관성센서 기반의 상체 분절간 상대위치 추정", 한국정밀공학회지, 38(3), pp.215~222 (2021), 한국정밀공학회[DOI]
- G. Wu, "ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion—Part II : shoulder, elbow, wrist and hand", J. Biomech, 38(5), pp.981~992 (2005)