Analysis of radar human gait signatures

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Analysis of radar human gait signatures

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The authors develop methods for the time–frequency (TF) analysis of human gait radar signals. In particular the authors demonstrate how knowledge of different motion classes can be obtained via a Markov chain model of state transitions based on the TF envelope structure associated with the motion sequence being analysed. The class-conditional knowledge thus obtained allows us to effectively extract the motion curves associated with different body parts via a non-parametric partial tracking algorithm that is coupled with an optimum Gaussian g-Snake modelling of the TF structure. The optimum segmentation of the TF structure into different half-cycles as well as the determination of the initial Doppler control points (corresponding to each half-cycle) is facilitated by a dynamic programming algorithm wherein the associated cost function involves a mean-square minimisation of the best quadratic fit to each segment together with a sparsity prior that enables us to control the smoothness of the approximation space in which the time series being analysed is effectively projected. Finally, the authors describe some of the limitations of our approach and point out future research directions that can overcome some of the difficulties associated with the complex interaction between the inherently non-linear dynamics of human gait motion and radar systems.

Inspec keywords: minimisation; time series; time-frequency analysis; Markov processes; dynamic programming; gait analysis; radar

Other keywords: Doppler control points; time-frequency analysis; time series; human gait motion; Gaussian g-Snake modelling; Markov chain model; radar human gait signature analysis; partial tracking algorithm; radar systems; mean-square minimisation; dynamic programming algorithm

Subjects: Optimisation techniques; Radar equipment, systems and applications; Markov processes

References

    1. 1)
      • Raj, R.G., Chen, V.C., Lipps, R.: `Analysis of human radar dismount signatures via parametric and non-parametric methods', IEEE Radar Conf., Pasadena, CA, 2009.
    2. 2)
      • K.J. Simpson , P. Jiang , P. Shewokis , S. Odum , K. Reeves . Kinematic and plantar pressure adjustments to downhill gradients during gait. Gait Posture , 172 - 179
    3. 3)
      • T.B. Moeslund , A. Hilton , V. Krueger . A survey of recent advances in vision-based human motion capture and analysis. Int. J. Comput. Vis. Image Underst. , 4 , 90 - 127
    4. 4)
      • P. van Dorp , F.C.A. Groen . Feature-based human motion parameter estimation with radar. IEE Proc., Radar Sonar Navig. , 2 , 135 - 145
    5. 5)
      • D.R. Wehner . (1995) High-resolution radar.
    6. 6)
      • T.H. Cormen , C.E. Leiserson , R.L. Rivest , C. Stein . (2009) Introduction to algorithms.
    7. 7)
      • CMU (Carnegie Mellon University) Motion Database: http://mocap.cs.cmu.edu/.
    8. 8)
      • Chen, V.C.: `Detection and analysis of human motion by radar', 2008 IEEE Radar Conf., 2008, Rome, Italy.
    9. 9)
      • D.C. Shapiro , R.F. Zernicke , R.J. Gregor , J.D. Diestel . Evidence of generalized motor programs using gait pattern analysis. J. Motor Behav. , 1 , 33 - 47
    10. 10)
      • Y. Hurmuzlu , C. Basdogan , J.J. Carollo . Presenting joint kinematics of human locomotion using phase plane portraits and Poincare maps. J. Biomech. , 12 , 1495 - 1499
    11. 11)
      • V.C. Chen , H. Ling . (2002) Time-frequency transforms for radar imaging and signal analysis.
    12. 12)
      • R.J. McAulay , T.F. Quatieri . Speech analysis/synthsis based on a sinsoidal representation. IEEE Trans. Acoust., Speech Signal Process. , 4 , 744 - 754
    13. 13)
      • J.W. Snellen . External work in level and grade walking on a motor-driven treadmill. J. Appl. Physiol. , 759 - 763
    14. 14)
      • N.A. Borghese , L. Bianchi , F. Lacquaniti . Kinematic determinants of human locomotion. J. Physiol. , 3 , 863 - 879
    15. 15)
      • P. Cavanagh . (1990) Biomechanics of distance running.
    16. 16)
      • A. Papoulis . (1991) Probability, random variables and stochastic processes.
    17. 17)
    18. 18)
      • Chen, V.C.: `Analysis of radar micro-Doppler signature with time-frequency transform', Proc. IEEE Workshop on Statistical Signal and Array Processing (SSAP), 2000, Pocono, PA, p. 463–466.
    19. 19)
      • A.C. Bobbert . Energy expenditure in level and grade walking. J. Appl. Physiol. , 1015 - 1021
    20. 20)
      • M. Milner , D. Dall , V.A. McConnel , P.K. Brennan , C. Hershler . Angle diagrams in the assessment of locomotor function. S.A. Med. J. , 951 - 957
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