Quantifying Chaotic Behavior in Treadmill Walking

详细信息    查看全文

• 作者：Henryk Josi艅ski (8)
  Agnieszka Michalczuk (7)
  Adam 艢wito艅ski (7) (8)
  Romualda Mucha (9)
  Konrad Wojciechowski (7)
  
  8. Institute of Informatics ; Silesian University of Technology ; Akademicka 16 ; 44-100 ; Gliwice ; Poland
  7. Polish-Japanese Academy of Information Technology ; Aleja Legion贸w 2 ; 41-902 ; Bytom ; Poland
  9. Medical University of Silesia ; Batorego 15 ; 41-902 ; Bytom ; Poland
  
• 关键词：Nonlinear time series analysis ; Phase space reconstruction ; Deterministic chaos ; Human motion analysis
• 刊名：Lecture Notes in Computer Science
• 出版年：2015
• 出版时间：2015
• 年：2015
• 卷：9012
• 期：1
• 页码：317-326
• 全文大小：434 KB
• 参考文献：1. Henry, B., Lovell, N., Camacho, F.: Nonlinear dynamics time series analysis. In: Akay, M.(ed.) Nonlinear Biomedical Signal Processing: Dynamic Analysis and Modeling, vol. 2, pp. 1鈥?9. Wiley Online Library (2012) (published online)
  2. Chen, C.-K., Lin, C.-L., Chiu, Y.-M.: Individual identification based on chaotic electrocardiogram signals. In: 6th IEEE Conference on Industrial Electronics and Applications, pp. 1765鈥?770 (2011)
  3. Cohen, M.E.: Chaos. Wiley Encyclopedia of Biomedical Engineering (2006)
  4. Osowski, S, 艢widerski, B, Cichocki, A, Rysz, A (2007) Epileptic seizure characterization by Lyapunov exponent of EEG signal. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 26: pp. 1276-1287 k" title="It opens in new window">CrossRef
  5. Mormann, F, Andrzejak, RG, Elger, CE, Lehnertz, K (2007) Seizure prediction: the long and winding road. Brain 130: pp. 314-333 k" title="It opens in new window">CrossRef
  6. Dingwell, JB, Cusumano, JP (2000) Nonlinear time series analysis of normal and pathological human walking. Chaos 10: pp. 848-863 k" title="It opens in new window">CrossRef
  7. Dingwell, JB, Marin, LC (2006) Kinematic variability and local dynamic stability of upper body motions when walking at different speeds. Journal of Biomechanics 39: pp. 444-452 k" title="It opens in new window">CrossRef
  8. Terrier, P, Deriaz, O (2013) Non-linear dynamics of human locomotion: effects of rhythmic auditory cueing on local dynamic stability. Frontiers in Physiology 4: pp. 1-13 k" title="It opens in new window">CrossRef
  9. England, SA, Granata, KP (2007) The influence of gait speed on local dynamic stability of walking. Gait & Posture 25: pp. 172-178 k" title="It opens in new window">CrossRef
  10. Look, N, Arellano, CJ, Grabowski, AM, McDermott, WJ, Kram, R, Bradley, E (2013) Dynamic stability of running: The effects of speed and leg amputations on the maximal lyapunov exponent. Chaos 23: pp. 043131 k" title="It opens in new window">CrossRef
  11. Hurmuzlu, Y, Basdogan, C, Stoianovici, D (1996) Kinematics and Dynamic Stability of the Locomotion of Post-Polio Patients. Journal of Biomechanical Engineering 118: pp. 405-411 k" title="It opens in new window">CrossRef
  12. Dingwell, JB, Kang, HG (2007) Differences Between Local and Orbital Dynamic Stability During Human Walking. Journal of Biomechanical Engineering 129: pp. 586-593 k" title="It opens in new window">CrossRef
  13. Arif, M, Ohtaki, Y, Nagatomi, R, Inooka, H (2004) Estimation of the Effect of Cadence on Gait Stability in Young and Elderly People using Approximate Entropy Technique. Measurement Science Review 4: pp. 29-40
  14. Stergiou, N, Moraiti, C, Giakas, G, Ristanis, S, Georgoulis, AD (2004) The effect of the walking speed on the stability of the anterior cruciate ligament deficient knee. Clinical Biomechanics 19: pp. 957-963 k" title="It opens in new window">CrossRef
  15. Georgoulis, AD, Moraiti, C, Ristanis, S, Stergiou, N (2006) A novel approach to measure variability in the anterior cruciate ligament deficient knee during walking: the use of the approximate entropy in orthopaedics. Journal of Clinical Monitoring and Computing 20: pp. 11-18 k" title="It opens in new window">CrossRef
  16. Perc, M (2005) The dynamics of human gait. European Journal of Physics 26: pp. 525-534 k" title="It opens in new window">CrossRef
  17. Takens, F.: Detecting Strange Attractor in Turbulence. Lecture Nodes in Mathematics, vol. 898, pp. 366鈥?81 (1981)
  18. Kugiumtzis, D (1996) State Space Reconstruction Parameters in the Analysis of Chaotic Time Series - the Role of the Time Window Length. Physica D: Nonlinear Phenomena 95: pp. 13-28 k" title="It opens in new window">CrossRef
  19. Kennel, MB, Brown, R, Abarbanel, HDI (1992) Determining embedding dimension for phase-space reconstruction using a geometrical construction. Physical Review A 45: pp. 3403-3411 k" title="It opens in new window">CrossRef
  20. Weisstein, E.W.: Attractor From MathWorld - A Wolfram Web Resource. http://mathworld.wolfram.com/Attractor.html
  21. Rosenstein, MT, Collins, JJ, Luca, CJ (1993) A practical method for calculating largest Lyapunov exponents from small data sets. Physica D 65: pp. 117-134 k" title="It opens in new window">CrossRef
  22. Awrejcewicz, J., Mosdorf, R.: Numerical Analysis of Some Problems of Chaotic Dynamics. WNT (2003)
  23. Webpage of the Human Motion Laboratory of the Polish-Japanese Academy of Information Technology. k.edu.pl" class="a-plus-plus">http://hm.pjwstk.edu.pl
  24. Toebes, MJP, Hoozemans, MJM, Furrer, R, Dekker, J, Die毛n, JH (2012) Local dynamic stability and variability of gait are associated with fall history in elderly subjects. Gait & Posture 36: pp. 527-531 k" title="It opens in new window">CrossRef
  
• 作者单位：Intelligent Information and Database Systems
• 丛书名：978-3-319-15704-7
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

The authors describe an example of application of nonlinear time series analysis directed at identifying the presence of deterministic chaos in human motion data by means of the largest Lyapunov exponent (LLE). The research aimed at determination of the influence of gait speed on the LLE value with a view to verification of the belief that slower walking leads to increased stability characterized by smaller LLE value. Analyses were focused on the time series representing hip flexion/extension angle, knee flexion/extension angle and dorsiflexion/plantarflexion dimension of the ankle. Gait sequences were recorded in the Human Motion Laboratory (HML) of the Polish-Japanese Academy of Information Technology in Bytom by means of the Vicon system. Application of the AC5000M treadmill allowed recordings in three variants: at the preferred walking speed (PWS) of each subject, at 80% of the PWS and at 120% of the PWS. According to the recommendations from the literature the LLE value was estimated twice for every time series: as the short-term LLE \(_1\) for the first stride and as the long-term LLE \(_{4-10}\) over a fixed interval between the fourth and the tenth stride. In the latter case it was confirmed that the LLE value increases with walking speed for both limbs.