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The Study to Track Human Arm Kinematics Applying Solutions of Wahba’s Problem upon Inertial/Magnetic Sensors

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Inclusive Smart Cities and Digital Health (ICOST 2016)

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Abstract

Long-term, off-site human monitoring systems are emerging with respect to the skyrocketing expenditures engaged with rehabilitation therapies for neurological diseases. Inertial/magnetic sensor modules are well known as a worthy solution for this problem. Much attention and effort are being paid for minimizing drift problem of angular rates, yet the rest of kinematic measurements (earth’s magnetic field and gravitational orientation) are only themselves capable enough to track movements applying the theory for solving historical Wahbas Problem. Further, these solutions give a closed form solution which makes it mostly suitable for real time Mo-Cap systems. This paper examines the feasibility of some typical solutions of Wahba’s Problem named TRIAD method, Davenport’s q method, Singular Value Decomposition method and QUEST algorithm upon current inertial/magnetic sensor measurements for tracking human arm movements. Further, the theoretical assertions are compared through controlled experiments with both simulated and actual accelerometer and magnetometer measurements.

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References

  1. Wahba, G.: A least squares estimate of satellite attitude. SIAM Rev. 7(3), 409 (1965)

    Article  Google Scholar 

  2. Markley, F.L., Mortari, D.: Quaternion attitude estimation using vector observations. J. Astronaut. Sci. 48(2), 359–380 (2000)

    Google Scholar 

  3. Markley, F.L., Mortari, D.: How to estimate attitude from vector observations (1999)

    Google Scholar 

  4. Lima, S.M.R.C.P.: Comparison of small satellite attitude determination methods (2000)

    Google Scholar 

  5. Markley, F.L., Crassidis, J.L.: Fundamentals of Spacecraft Attitude Determination and Control. Springer, New York (2014)

    Book  MATH  Google Scholar 

  6. Yun, X., Bachmann, E.: Design, implementation, and experimental results of a quaternion-based kalman filter for human body motion tracking. IEEE Trans. Rob. 22(6), 1216–1227 (2006)

    Article  Google Scholar 

  7. Karunarathne, M.S., Ekanayake, S.W., Pathirana, P.N.: An adaptive complementary filter for inertial sensor based data fusion to track upper body motion. In: 2014 7th International Conference on Information and Automation for Sustainability (ICIAfS), pp. 1–5. IEEE (2014)

    Google Scholar 

  8. Shuster, M.D.: A survey of attitude representations. Navigation 8(9), 439–517 (1993)

    MathSciNet  Google Scholar 

  9. Shuster, M.D., Dellinger, W.F.: Spacecraft attitude determination and control. In: Fundamentals of Space Systems, pp. 236–325 (1994)

    Google Scholar 

  10. Wertz, J.R.: Spacecraft Attitude Determination and Control. Springer Science & Business Media, Heidelberg (2012)

    Google Scholar 

  11. Sidi, M.J.: Spacecraft dynamics, control: a practical engineering approach. Cambridge University Press, Cambridge (1997)

    Book  Google Scholar 

  12. Black, H.D.: Early development of transit, the navy navigation satellite system. J. Guidance, Control Dyn. 13(4), 577–585 (1990)

    Article  MathSciNet  Google Scholar 

  13. Hajiyev, C., Cilden, D., Somov, Y.: Gyroless attitude and rate estimation of small satellites using singular value decomposition and extended kalman filter. In: 2015 16th International Carpathian Control Conference (ICCC), pp. 159–164, May 2015

    Google Scholar 

  14. Markley, F.L.: Attitude determination using vector observations and the singular value decomposition. J. Astronaut. Sci. 36(3), 245–258 (1988)

    MathSciNet  Google Scholar 

  15. Moon, F.C.: The Machines of Leonardo Da Vinci and Franz Reuleaux: kinematics of machines from the Renaissance to the 20th Century. Springer, Netherlands (2007)

    Book  MATH  Google Scholar 

  16. Davenport, P.B.: A vector approach to the algebra of rotations with applications. National Aeronautics and Space Administration, vol. 4696 (1968)

    Google Scholar 

  17. Shuster, M.D.: Approximate algorithms for fast optimal attitude computation. In: Guidance and Control Conference, vol. 1, pp. 88–95 (1978)

    Google Scholar 

  18. Markley, F.L.: Equivalence of two solutions of wahbas problem. J. Astronaut. Sci. 60(3–4), 303–312 (2013)

    Article  Google Scholar 

  19. Tseng, S.P., Li, W.-L., Sheng, C.-Y., Hsu, J.-W., Chen, C.-S.: Motion and attitude estimation using inertial measurements with complementary filter. In: Control Conference (ASCC): 8th Asian, pp. 863–868. IEEE (2011)

    Google Scholar 

  20. van Exel, N.J.A., Koopmanschap, M.A.: Cost-effectiveness of integrated stroke services. J. Med. 98(6), 415–425 (2005)

    Google Scholar 

  21. Flenniken, W., Wall, J., Bevly, D.: Characterization of various IMU error sources and the effect on navigation performance. In: ION GNSS, pp. 967–978 (2005)

    Google Scholar 

  22. Biokin. http://biokin.com.au/

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Correspondence to M. Sajeewani Karunarathne .

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Karunarathne, M.S., Nguyen, N.D., Menikidiwela, M.P., Pathirana, P.N. (2016). The Study to Track Human Arm Kinematics Applying Solutions of Wahba’s Problem upon Inertial/Magnetic Sensors. In: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_35

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  • DOI: https://doi.org/10.1007/978-3-319-39601-9_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39600-2

  • Online ISBN: 978-3-319-39601-9

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