Browse > Article
http://dx.doi.org/10.46670/JSST.2022.31.3.156

Effects of the Selection of Deformation-related Variables on Accuracy in Relative Position Estimation via Time-varying Segment-to-Joint Vectors  

Lee, Chang June (Mechanical Engineering, Hankyong National University)
Lee, Jung Keun (School of ICT, Robotics & Mechanical Engineering, Hankyong National University)
Publication Information
Journal of Sensor Science and Technology / v.31, no.3, 2022 , pp. 156-162 More about this Journal
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 deformation-related variables for the sternum-to-upper arm and upper arm-to-forearm, respectively. Furthermore, the case with multiple deformation-related variables was superior by an average of 2.19 mm compared to the case with a single variable.
Keywords
Relative position estimation; Segment-to-joint vector; Deformation-related variable; Non-rigidity;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 J. K. Lee, "A parallel attitude-heading Kalman filter without state-augmentation of model-based disturbance components", IEEE Trans. Instrum. Meas., Vol. 68, No. 7, pp. 2668-2670, 2019.   DOI
2 T. Seel, T. Schauer, and J. Raisch, "Joint axis and position estimation from inertial measurement data by exploiting kinematic constraints", Proc. of IEEE Int. Conf. Control Appl., pp. 45-49, Dubrovnik, Croatia, 2012.
3 D. L. Benoit, M. Damsgaard, and M. S. Andersen, "Surface marker cluster translation, rotation, scaling and deformation: Their contribution to soft tissue artefact and impact on knee joint kinematics", J. Biomech., Vol. 48, No. 10, pp. 2124-2129, 2015.   DOI
4 G. Wu, F. C. Van der Helm, H. D. Veeger, M. Makhsous, P. Van Roy, C. Anglin, J. Nagels, A. R. Karduna, K. McQuade, X. Wang, F. W. Werner, and B. Buchholz, "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., Vol. 38, No. 5, pp. 981-992, 2005.   DOI
5 W. C. Jung and J. K. Lee, "Comparison of drift reduction methods for pedestrian dead reckoning based on a shoemounted IMU", J. Sens. Sci. Technol., Vol. 28, No. 6, pp. 345-354, 2019.   DOI
6 C. J. Lee and J. K. Lee, "Wearable IMMU-based relative position estimation between body segments via time-varying segment-to-joint vectors", Sensors, Vol. 22, No. 6, pp. 2149, 2022.   DOI
7 C. J. Lee and J. K. Lee, "Relative position estimation using Kalman filter based on inertial sensor signals considering soft tissue artifacts of human body segments", J. Sens. Sci. Technol., Vol. 29, No. 4, pp. 237-242, 2020.   DOI
8 F. D'Isidoro, C. Brockmann, and S. J. Ferguson, "Effects of the soft tissue artefact on the hip joint kinematics during unrestricted activities of daily living", J. Biomech., Vol. 104, pp. 109717(1)-109717(10), 2020.
9 E. Grimpampi, V. Camomilla, A. Cereatti, P. De Leva, and A. Cappozzo, "Metrics for describing soft-tissue artefact and its effect on pose, size, and shape of marker clusters", IEEE Trans. Biomed. Eng., Vol. 61, No. 2, pp. 362-367, 2013.   DOI
10 Y. Zheng, K. C. Chan, and C. C. Wang, "Pedalvatar: An IMU-based real-time body motion capture system using foot rooted kinematic model", Proc. of 2014 IEEE/RSJ Int. Conf. Intell. Robot. Syst., pp. 4130-4135, Chicago, Illinois, USA, 2014.
11 S. G. de Villa, A. J. Martin, and J. J. G. Dominguez, "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.
12 H. G. Kortier, J. Antonsson, H. M. Schepers, F. Gustafsson, and P. H. Veltink, "Hand pose estimation by fusion of inertial and magnetic sensing aided by a permanent magnet", IEEE Trans. Neural Syst. Rehabil. Eng., Vol. 23, No. 5, pp. 796-806, 2014.   DOI
13 J. Cameron and J. Lasenby, "A real-time sequential algorithm for human joint localization", Proc. of ACM SIGGRAPH 2005 Posters, pp. 107, New York, USA, 2005.
14 M. S. Lee, H. Ju, J. W. Song, and C. G. Park, "Kinematic model-based pedestrian dead reckoning for heading correction and lower body motion tracking", Sensors, Vol. 15, No. 11, pp. 28129-28153, 2015.   DOI
15 G. Pons-Moll, A. Baak, T. Helten, M. Muller, H. Seidel, and B. Rosenhahn, "Multisensor-fusion for 3D full-body human motion capture", Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pp. 663-670, San Francisco, CA, USA, 2010.
16 M. Kok, J. D. Hol, and T. B. Schon, "An optimization-based approach to human body motion capture using inertial sensors", Proc. of 19th World Congr. Int. Federation Autom. Control, pp. 79-85, Cape Town, South Africa, 2014.
17 H. Zhou, H. Hu, and Y. Tao, "Inertial measurements of upper limb motion", Med. Biol. Eng. Comput., Vol. 44, No. 6, pp. 479-487, 2006.   DOI
18 A. Atrsaei, H. Salarieh, A. Alasty, and M. Abediny, "Human arm motion tracking by inertial/magnetic sensors using unscented Kalman filter and relative motion constraint", J. Intell. Robot. Syst., Vol. 90, No. 1, pp. 161-170, 2018.   DOI
19 J. K. Lee, "Verification of two least-squares methods for estimating center of rotation using optical marker trajectory", J. Sens. Sci. Technol., Vol. 26, No. 6, pp. 371-378, 2017.   DOI
20 C. J. Lee and J. K. Lee, "Inertial sensor-based relative position estimation between upper body segments considering non-rigidity of human bodies", J. Korean Soc. Precis. Eng., Vol. 38, No. 3, pp. 215-222, 2021.   DOI
21 D. Roetenberg, P. J. Slycke, and P. H. Veltink, "Ambulatory position and orientation tracking fusing magnetic and inertial sensing", IEEE Trans. Biomed. Eng., Vol. 54, No. 5, pp. 883-890, 2007.   DOI
22 J. K. Lee and E. J. Park, "A fast quaternion-based orientation optimizer via virtual rotation for human motion tracking", IEEE Trans. Biomed. Eng., Vol. 56, No. 5, pp. 1574-1582, 2008.   DOI
23 H. J. Luinge and P. H. Veltink, "Measuring orientation of human body segments using miniature gyroscopes and accelerometers", Med. Biol. Eng. Comput., Vol. 43, No. 2, pp. 273-282, 2005.   DOI