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Research Papers

A Mobile Motion Capture System Based on Inertial Sensors and Smart Shoes

[+] Author and Article Information
Pyeong-Gook Jung

e-mail: pgjung@sogang.ac.kr

Sehoon Oh

Research Professor
e-mail: sehoon74@sogang.ac.kr
Department of Mechanical Engineering,
Sogang University,
Seoul 121-742, Korea

Gukchan Lim

Chief Research Engineer
Mobile Handset R&D Center,
LG Electronics,
Seoul 153-801, Korea
e-mail: gukchan.lim@lge.com

Kyoungchul Kong

Assistant Professor
Department of Mechanical Engineering,
Sogang University,
Seoul 121-742, Korea
e-mail: kckong@sogang.ac.kr

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 23, 2012; final manuscript received August 1, 2013; published online August 30, 2013. Assoc. Editor: Sergey Nersesov.

J. Dyn. Sys., Meas., Control 136(1), 011002 (Aug 30, 2013) (9 pages) Paper No: DS-12-1388; doi: 10.1115/1.4025207 History: Received November 23, 2012; Revised August 01, 2013

Motion capture systems play an important role in health-care and sport-training systems. In particular, there exists a great demand on a mobile motion capture system that enables people to monitor their health condition and to practice sport postures anywhere at any time. The motion capture systems with infrared or vision cameras, however, require a special setting, which hinders their application to a mobile system. In this paper, a mobile three-dimensional motion capture system is developed based on inertial sensors and smart shoes. Sensor signals are measured and processed by a mobile computer; thus, the proposed system enables the analysis and diagnosis of postures during outdoor sports, as well as indoor activities. The measured signals are transformed into quaternion to avoid the Gimbal lock effect. In order to improve the precision of the proposed motion capture system in an open and outdoor space, a frequency-adaptive sensor fusion method and a kinematic model are utilized to construct the whole body motion in real-time. The reference point is continuously updated by smart shoes that measure the ground reaction forces.

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References

Steffen, Lyn. M., Arnett, Donna, K., Blackbern, H., Shah, G., Armstrong, C., Luepker, R. V., and Jacobs, David R., 2006, “Population Trends in Leisure-Time Physical Activity: Minnesota Hear Survey, 1980–2000,” Med. Sci. Sports Exercise, 38(10), pp. 1716–1723. [CrossRef]
Chong, A. Y.-L., and Chan, FelixT. S., 2012, “Structural Equation Modeling for Multi-Stage Analysis on Radio Frequency Identification (RFID) Diffusion in the Health Care Industry,” Expert Sys. Applic., 39(10), pp. 8645–8654. [CrossRef]
Macintosh, E., and Walker, M., 2012, “Chronicling the Transient Nature of Fitness Employees: An Organizational Culture Perspective,” J. Sport Manag., 26(2), pp.113–126.
Sport Research Intelligence Sportive, accessed on Aug. 2012, http://secure.sirc.ca
Zetou, E., Koronas, V., Athanailidis, I., and Koussis, P., 2012, “Learning Tennis Skill Through Game Play and Stay in Elementary Pupils,” J. Hum. Sport Exerc., 7(2), pp. 560–572. [CrossRef]
Clara, S.Lewis, 2008, “Life Chances and Wellness: Meaning and Motivation in the “Yoga Market,” Sport Soc., 11(5), pp. 535–545. [CrossRef]
Chan, J. C. P., Leung, H., TangJ. K. T., and Komura, T., 2011, “A Virtual Reality Dance Training System Using Motion Capture Technology,” IEEE Trans. Learn. Technol., 4(2), pp. 187–195. [CrossRef]
Golf Teaching and Research Center, accessed on Aug. 2012, http://www.hhdev.psu.edu/rptm/gtrc
Taylor Made Performance Labs, accessed on Aug. 2012, http://www.tmplabs.com/
Callaway Golf Performance Center, accessed on Aug. 2012, http://www.callawaygolf.com/
Kong, K., and Tomizuka, M., 2009, “A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe,” IEEE/ASME Trans. Mechatron., 14(3), pp. 358–370. [CrossRef]
Brigante, C. M. N., Abbate, N., Basile, A., Faulisi, A. C., and Sessa, S., 2011, “Towards Miniaturization of a MEMS-Based Wearable Motion Capture System,” IEEE Trans. Ind. Electron., 58(8), pp. 3234–3241. [CrossRef]
Hashi, S., Tokunaga, Y., Yabukami, S., Toyoda, M., Ishiyama, K., Okazaki, Y., and Arai, K. I., 2005, “Development of Real-Time and Highly Accurate Wireless Motion Capture System Utilizing Soft Magnetic Core,” IEEE Trans. Magn., 41(10), pp. 4191–4193. [CrossRef]
Kwon, S., Park, H.-S., Stanley, C. J., Kim, J., Kim, J.-H., and Damiano, D. L., 2012, “A Practical Strategy for sEMG-Based Knee Joint Moment Estimation During Gait and Its Validation in Individuals With Cerebral Palsy,” IEEE Trans. Biomed. Eng., 59(5), pp. 1480–1487. [CrossRef] [PubMed]
Fourati, H., Manamanni, N., Afilal, L., and Handrich, Y., “Complementary Observer for Body Segments Motion Capturing by Inertial and Magnetic Sensors,” IEEE/ASME Trans. Mechatron. (accepted).
Zhang, Z.-Q., and Wu, J.-K., 2011, “A Novel Hierarchical Information Fusion Method for Three-Dimensional Upper Limb Motion Estimation,” IEEE Trans. Instrum. Meas., 60(11), pp. 3709–3719. [CrossRef]
Frosio, I., Pedersini, F., and Borghese, N. A., 2009, “Autocalibration of MEMS Accelerometers,” IEEE Trans. Instrum. Meas., 58(6), pp. 2034–2041. [CrossRef]
Zhou, H., and Hu, H., 2010, “Reducing Drifts in the Inertial Measurements of Wrist and Elbow Positions,” IEEE Trans. Instrum. Meas., 59(3), pp. 575–585. [CrossRef]
Miller, N., Jenkins, O. C., Kallmann, M., and Mataric, M. J., 2004, “Motion Capture From Inertial Sensing for Untethered Humanoid Teleoperation,” IEEE International Conference on Humanoid Robots, Vol. 2, pp. 547–565.
Brodie, M., Walmsley, A., and Page, W., 2008, “Fusion Motion Capture: A Prototype System Using Inertial Measurement Units and GPS for the Biomechanical Analysis of Ski Racing,” Sports Technol., 1(1), pp. 17–28. [CrossRef]
Xsens, accessed on Nov. 2012, http://www.xsens.com/
Life Performance Research, accessed on Nov. 2012, http://www.lp-research.com/
EBMotion, E2BOX, accessed on Nov. 2012, http://www.e2box.co.kr/
Lin, Z., Zecca, M., Sessa, S., Bartolomeo, L., Ishii, H., and Itoh, K., 2010, “Development of an Ultra-Miniaturized Inertial Measurement Unit WB-3 for Human Body Motion Tracking,” IEEE International Symposium on System Integration, pp. 414–419.
Lepetit, V., and Fua, P., 2005, “Monocular Model-Based 3D Tracking of Rigid Objects,” Found. Trends. Comput. Graph. Vision, 1(1), pp. 11–14 [CrossRef].
Winter, D. A., 2004, Biomechanics and Motor Control of Human Movement, 3rd ed., John Wiley and Sons, Inc., Hoboken, NJ.
Wone, S.-H. P., Melek, W. W., and Golnaraghi, F., 2010, “A Kalman/Particle Filter-Based Position and Orientation Estimation Method Using a Position Sensor/Inertial Measurement Unit Hybrid System,” IEEE Trans. Instrum. Meas., 57(5), pp. 1787–1798 [CrossRef].

Figures

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Fig. 1

Orientation of a body segment; (a) quaternion, (b) roll (θ), pitch (ϕ), and yaw (ψ)

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Fig. 2

Position vectors for constructing the whole body motion; (a) a neutral posture, (b) an arbitrary posture. In (b), (k) is omitted for some vectors for the simplicity of representation

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Fig. 3

A set of an IMU and a data receiver; (a) an IMU, (b) a wireless data receiver. In (a), a quarter coin is shown for comparison of the size

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Fig. 4

Sensor installation position and orientation; (a) gyroscope and (b) accelerometer

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Fig. 5

The block diagram of sensor fusion

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Fig. 6

A cut-off frequency with respect to the acceleration magnitude

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Fig. 7

A smart shoe for detecting reference points; (a) a smart shoe, (b) the insole of the smart shoe

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Fig. 8

A scene of experiments; (a) a human subject and (b) a captured motion

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Fig. 9

Sensor fusion results for one-dimensional test; (a) pitch angle and (b) acceleration magnitude

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Fig. 10

Ground reaction forces and motion phases

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Fig. 11

Captured motions; (a) a sitting state, (b) sit-to-stand, and (c) walking

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Fig. 12

An experimental setup for performance verification

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Fig. 13

Experimental results; (a) slow motion and (b) fast motion

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Fig. 14

An evaluation methods of the proposed motion capture system

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