Transactions of the Korean Society of Mechanical Engineers A (대한기계학회논문집A)

The Korean Society of Mechanical Engineers (대한기계학회)
권호 표지
DOI QR코드

DOI QR Code

Chaos Analysis of Major Joint Motions for Young Males During Walking

보행시 젊은 남성에 대한 상.하체 주요 관절 운동의 카오스 분석

  • 박정홍 (부산대학교 기계기술연구소) ;
  • 김광훈 (부산대학교 기계설계대학원) ;
  • 손권 (부산대학교 기계공학부)
  • Published : 2007.08.01
Download PDF
⟨ Previous Next ⟩

Abstract

Quantifying dynamic stability is important to assessment of falling risk or functional recovery for leg injured people. Human locomotion is complex and known to exhibit nonlinear dynamical behaviors. The purpose of this study is to quantify major joints of the body using chaos analysis during walking. Time series of the chaotic signals show how gait patterns change over time. The gait experiments were carried out for ten young males walking on a motorized treadmill. Joint motions were captured using eight video cameras, and then three dimensional kinematics of the neck and the upper and lower extremities were computed by KWON 3D motion analysis software. The correlation dimension and the largest Lyapunov exponent were calculated from the time series to quantify stabilities of the joints. This study presents a data set of nonlinear dynamic characteristics for eleven joints engaged in normal level walking.

Keywords

References

  1. Dingwell, J. B. and Cusumano, J. P., 2000, 'Nonlinear Time Series Analysis of Normal and Pathological Human Walking,' Chaos, Vol. 10, No. 4, pp. 848 - 863 https://doi.org/10.1063/1.1324008
  2. Dingwell, J. B., and Marin, L. C., 2006, 'Kinematic Variability and Local Dynamic Stability of Upper Body Motions When Walking at Different Speeds,' Journal of Biomechanics, Vol. 39, pp. 444-452 https://doi.org/10.1016/j.jbiomech.2004.12.014
  3. Dingwell, J. B., and Cavanagh, P. R., 2001, 'Increased Variability of Continous Overground Walking in Neuropathic Patients is Only Indirectly Related to Sensory Loss,' Gait and Posture, Vol. 14, pp. 1-10 https://doi.org/10.1016/S0966-6362(01)00101-1
  4. Chung, D., Sim, Y., Yi, S., Shin, J., Kim, S., Kim, C. and Kim, S., 2000, 'Nonlinear Dynamic and Chaotic Analysis of Fetal Heart Rate in Fetal Distress,' Korean Journal of Obsterics and Gynecology, Vol. 43, No.6, pp. 1071-1079
  5. Choi, B. K., Kim, B. C., and Shin C. W., 2006, 'Introduction to Chaos Analysis Method of Time Series Signal: With Priority Given to Oceanic Underwater Ambient Noise Signal,' Ocean and Polar Research, Vol. 28, No.4, pp. 459-465 https://doi.org/10.4217/OPR.2006.28.4.459
  6. Harboume, R. T., and Stergiou, N., 2003, 'Nonlinear Analysis of the Development of Sitting Postural Control,' Developmental Psychobiology, Vol. 42, pp. 368--677 https://doi.org/10.1002/dev.10110
  7. Stergiou, N., Moraiti, C., Giakas, G., Ristanis, S. and Georgoulis, A. D., 2004, 'The Effect of the Walking Speed on the Stability of the Anterior Cruciate Ligament Deficient Knee,' Clinical Biomechanics, Vol. 19, No.9, pp. 957 -963 https://doi.org/10.1016/j.clinbiomech.2004.06.008
  8. Dingwell, J. B., Cusumano, J. P., Srernad, D. and Cavanagh, P. R., 2000, 'Slower Speeds in Patients with Diabetic Neuropathy Lead to Improved Local Dynamic Stability of Continuous Overground Walking,' Journal of Biomechanics. Vol. 33, No. 10, pp. 1269-1277 https://doi.org/10.1016/S0021-9290(00)00092-0
  9. Buzzi, U. H., Stergiou, N., Kurz, M. J., Hageman, P. A. and Heidel, J., 2004, 'Nonlinear Dynamics Indicates Aging Affects Variability During Gait,' Clinical Biomechanics, Vol. 18, No.5, pp. 435-443 https://doi.org/10.1016/S0268-0033(03)00029-9
  10. Ko, J. H., Son, K., Moon, B. Y. and Suh, J. T., 2006, 'Gait Study on the Normal and ACL Deficient Patients after Ligament Reconstruction Surgery Using Chaos Analysis,' Journal of KSPE, Vol. 30, No.4, pp. 435-441 https://doi.org/10.3795/KSME-A.2006.30.4.435
  11. Park, K. B., Ko, J. H., Son, K., Moon, B. Y. and Suh, J. T., 2006, 'Application of Chaos Theory to Gait Analysis,' Transection of KSME (A), Vol. 30, No.2, pp. 194-201 https://doi.org/10.3795/KSME-A.2006.30.2.194
  12. Jeong, J., Gore, J. C. and Peterson, B. S., 2001, 'Mutual Information Analysis of the EEG in Patients with Alzheimer's Disease,' Clinical Neurophysiology, Vol. 114, No.5, pp. 827-835 https://doi.org/10.1016/S1388-2457(01)00513-2
  13. Rhodes, C. and Morari, M., 1997, 'The False Nearest Neighbors Algorithm: An Overview,' Computers & Chemical Engineering, Vol. 21, No. 1, pp. 1149-1154 https://doi.org/10.1016/S0098-1354(97)00204-4
  14. Grassberger P. and Procaccia I., 1983, 'Characterization of Strange Attractors,' Physical Review Letters, Vol. 50, pp. 346-349 https://doi.org/10.1103/PhysRevLett.50.346
  15. Wolf, A., Swift, J. B., Swinney, H. L. and Vastano, J. A., 1985, 'Determining Lyapunov Exponents from a Time Series,' Physica D: Nonlinear Phenomena, Vol. 16, No.3, pp. 285-317 https://doi.org/10.1016/0167-2789(85)90011-9
  16. Sprott, J. C., and Rowlands, G., Chaos Data Analyzer: The Professional Version User's Manual, Physics Academic Software, Raleigh, North Carolina, pp. 20-23

Cited by

  1. Simple Pedestrian Localization Algorithms Based on Distributed Wireless Sensor Networks vol.56, pp.10, 2009, https://doi.org/10.1109/TIE.2009.2017097