Nonlinear time-series analysis of different human walking gaits

Sajid Iqbal; Xizhe Zang; Yanhe Zhu; Hanadi Mohammed Abass Ali Saad; Jie Zhao

doi:10.1109/EIT.2015.7293419

Nonlinear time-series analysis of different human walking gaits

Sajid Iqbal
, Xizhe Zang
, Yanhe Zhu
, Hanadi Mohammed Abass Ali Saad
, Jie Zhao

School of Mechatronics Engineering

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Human locomotion is a complex nonlinear process, which researchers have started to analyze using nonlinear dynamics analysis. This study investigates and quantifies the chaotic dynamics of walking gaits using different tools of nonlinear time-series analysis. The application of nonlinear dynamics techniques to gait cycle sequences may unveil the complexity of the human walking. For the walking gaits, calculated Lyapunov exponents and fractal dimensions suggested chaotic dynamics, which are intrinsic to human locomotor system. Such studies may open new avenues for research in gait pathologies and highlight the application of chaotic time-series analysis for examining physiological data.

Original language	English
Title of host publication	2015 IEEE International Conference on Electro/Information Technology, EIT 2015
Publisher	IEEE Computer Society
Pages	25-30
Number of pages	6
ISBN (Electronic)	9781479988020
DOIs	https://doi.org/10.1109/EIT.2015.7293419
State	Published - 10 Jun 2015
Event	IEEE International Conference on Electro/Information Technology, EIT 2015 - Dekalb, United States Duration: 21 May 2015 → 23 May 2015

Publication series

Name	IEEE International Conference on Electro Information Technology
Volume	2015-June
ISSN (Print)	2154-0357
ISSN (Electronic)	2154-0373

Conference

Conference	IEEE International Conference on Electro/Information Technology, EIT 2015
Country/Territory	United States
City	Dekalb
Period	21/05/15 → 23/05/15

Keywords

Chaos
dynamical systems
legged locomotion
nonlinear time-series analysis
state-space reconstruction
time-delay embedding

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10.1109/EIT.2015.7293419

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Iqbal, S., Zang, X., Zhu, Y., Saad, H. M. A. A., & Zhao, J. (2015). Nonlinear time-series analysis of different human walking gaits. In 2015 IEEE International Conference on Electro/Information Technology, EIT 2015 (pp. 25-30). Article 7293419 (IEEE International Conference on Electro Information Technology; Vol. 2015-June). IEEE Computer Society. https://doi.org/10.1109/EIT.2015.7293419

@inproceedings{78247cfe355e479c9d4ddcd0ae2950b1,

title = "Nonlinear time-series analysis of different human walking gaits",

abstract = "Human locomotion is a complex nonlinear process, which researchers have started to analyze using nonlinear dynamics analysis. This study investigates and quantifies the chaotic dynamics of walking gaits using different tools of nonlinear time-series analysis. The application of nonlinear dynamics techniques to gait cycle sequences may unveil the complexity of the human walking. For the walking gaits, calculated Lyapunov exponents and fractal dimensions suggested chaotic dynamics, which are intrinsic to human locomotor system. Such studies may open new avenues for research in gait pathologies and highlight the application of chaotic time-series analysis for examining physiological data.",

keywords = "Chaos, dynamical systems, legged locomotion, nonlinear time-series analysis, state-space reconstruction, time-delay embedding",

author = "Sajid Iqbal and Xizhe Zang and Yanhe Zhu and Saad, \{Hanadi Mohammed Abass Ali\} and Jie Zhao",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Electro/Information Technology, EIT 2015 ; Conference date: 21-05-2015 Through 23-05-2015",

year = "2015",

month = jun,

day = "10",

doi = "10.1109/EIT.2015.7293419",

language = "英语",

series = "IEEE International Conference on Electro Information Technology",

publisher = "IEEE Computer Society",

pages = "25--30",

booktitle = "2015 IEEE International Conference on Electro/Information Technology, EIT 2015",

address = "美国",

}

Iqbal, S, Zang, X , Zhu, Y, Saad, HMAA & Zhao, J 2015, Nonlinear time-series analysis of different human walking gaits. in 2015 IEEE International Conference on Electro/Information Technology, EIT 2015., 7293419, IEEE International Conference on Electro Information Technology, vol. 2015-June, IEEE Computer Society, pp. 25-30, IEEE International Conference on Electro/Information Technology, EIT 2015, Dekalb, United States, 21/05/15. https://doi.org/10.1109/EIT.2015.7293419

Nonlinear time-series analysis of different human walking gaits. / Iqbal, Sajid; Zang, Xizhe ; Zhu, Yanhe et al.
2015 IEEE International Conference on Electro/Information Technology, EIT 2015. IEEE Computer Society, 2015. p. 25-30 7293419 (IEEE International Conference on Electro Information Technology; Vol. 2015-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Nonlinear time-series analysis of different human walking gaits

AU - Iqbal, Sajid

AU - Zang, Xizhe

AU - Zhu, Yanhe

AU - Saad, Hanadi Mohammed Abass Ali

AU - Zhao, Jie

PY - 2015/6/10

Y1 - 2015/6/10

N2 - Human locomotion is a complex nonlinear process, which researchers have started to analyze using nonlinear dynamics analysis. This study investigates and quantifies the chaotic dynamics of walking gaits using different tools of nonlinear time-series analysis. The application of nonlinear dynamics techniques to gait cycle sequences may unveil the complexity of the human walking. For the walking gaits, calculated Lyapunov exponents and fractal dimensions suggested chaotic dynamics, which are intrinsic to human locomotor system. Such studies may open new avenues for research in gait pathologies and highlight the application of chaotic time-series analysis for examining physiological data.

AB - Human locomotion is a complex nonlinear process, which researchers have started to analyze using nonlinear dynamics analysis. This study investigates and quantifies the chaotic dynamics of walking gaits using different tools of nonlinear time-series analysis. The application of nonlinear dynamics techniques to gait cycle sequences may unveil the complexity of the human walking. For the walking gaits, calculated Lyapunov exponents and fractal dimensions suggested chaotic dynamics, which are intrinsic to human locomotor system. Such studies may open new avenues for research in gait pathologies and highlight the application of chaotic time-series analysis for examining physiological data.

KW - Chaos

KW - dynamical systems

KW - legged locomotion

KW - nonlinear time-series analysis

KW - state-space reconstruction

KW - time-delay embedding

UR - https://www.scopus.com/pages/publications/84975706732

U2 - 10.1109/EIT.2015.7293419

DO - 10.1109/EIT.2015.7293419

M3 - 会议稿件

AN - SCOPUS:84975706732

T3 - IEEE International Conference on Electro Information Technology

SP - 25

EP - 30

BT - 2015 IEEE International Conference on Electro/Information Technology, EIT 2015

PB - IEEE Computer Society

T2 - IEEE International Conference on Electro/Information Technology, EIT 2015

Y2 - 21 May 2015 through 23 May 2015

ER -

Nonlinear time-series analysis of different human walking gaits

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