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Research Papers

Using Entropy Measures to Characterize Human Locomotion

[+] Author and Article Information
Graham Leverick

Department of Mechanical Engineering,
University of Manitoba,
Winnipeg, MB R3T 5V6, Canada

Tony Szturm

School of Medical Rehabilitation,
University of Manitoba,
Winnipeg, MB R3E 0T6, Canada
e-mail: tony.szturm@med.umanitoba.ca

Christine Q. Wu

Department of Mechanical Engineering,
University of Manitoba,
Winnipeg, MB R3T 5V6, Canada
e-mail: christine.wu@umanitoba.ca

Manuscript received January 27, 2014; final manuscript received August 7, 2014; accepted manuscript posted August 27, 2014; published online October 17, 2014. Assoc. Editor: Paul Rullkoetter.

J Biomech Eng 136(12), 121002 (Oct 17, 2014) (8 pages) Paper No: BIO-14-1052; doi: 10.1115/1.4028410 History: Received January 27, 2014; Revised August 07, 2014; Accepted August 27, 2014

Entropy measures have been widely used to quantify the complexity of theoretical and experimental dynamical systems. In this paper, the value of using entropy measures to characterize human locomotion is demonstrated based on their construct validity, predictive validity in a simple model of human walking and convergent validity in an experimental study. Results show that four of the five considered entropy measures increase meaningfully with the increased probability of falling in a simple passive bipedal walker model. The same four entropy measures also experienced statistically significant increases in response to increasing age and gait impairment caused by cognitive interference in an experimental study. Of the considered entropy measures, the proposed quantized dynamical entropy (QDE) and quantization-based approximation of sample entropy (QASE) offered the best combination of sensitivity to changes in gait dynamics and computational efficiency. Based on these results, entropy appears to be a viable candidate for assessing the stability of human locomotion.

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Copyright © 2014 by ASME
Topics: Entropy
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References

Figures

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Fig. 1

Passive dynamic walking model

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Fig. 2

Experimental setup

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Fig. 3

Segmented and normalized pressure mat data: (a) medial–lateral and (b) anterior–posterior

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Fig. 4

Entropy versus perturbation size in walker model (with standard error)

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