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Technical Brief

Day-to-Day Reliability of Nonlinear Methods to Assess Walking Dynamics

[+] Author and Article Information
P. C. Raffalt

Julius Wolff Institute for Biomechanics and
Musculoskeletal Regeneration,
Charité—Universitätsmedizin Berlin,
Augustenburger Platz 1,
Berlin 13353, Germany;
Department of Biomedical Sciences,
University of Copenhagen,
Copenhagen 2200, Denmark
e-mail: peter-christian.raffalt@charite.de

T. Alkjær, B. Brynjólfsson, L. Jørgensen

Department of Biomedical Sciences,
University of Copenhagen,
Copenhagen 2200, Denmark

C. Bartholdy, M. Henriksen

The Parker Institute,
Copenhagen University Hospital Bispebjerg,
Frederiksberg 2000, Denmark;
Department of Physical and Occupational Therapy,
Copenhagen University Hospital Bispebjerg,
Frederiksberg 2000, Denmark

1Corresponding author.

Manuscript received October 11, 2017; final manuscript received July 23, 2018; published online September 25, 2018. Assoc. Editor: Tammy L. Haut Donahue.

J Biomech Eng 140(12), 124501 (Sep 25, 2018) (8 pages) Paper No: BIO-17-1460; doi: 10.1115/1.4041044 History: Received October 11, 2017; Revised July 23, 2018

The present study investigated the day-to-day reliability (quantified by the absolute and relative reliability) of nonlinear methods used to assess human locomotion dynamics. Twenty-four participants of whom twelve were diagnosed with knee osteoarthritis completed 5 min of treadmill walking at self-selected preferred speed on two separate days. Lower limb kinematics were recorded at 100 Hz and hip, knee, and ankle joint angles, three-dimensional (3D) sacrum marker displacement and stride time intervals were extracted for 170 consecutive strides. The largest Lyapunov exponent and correlation dimension were calculated for the joint angle and sacrum displacement data using three different state space reconstruction methods (group average, test-retest average, individual time delay and embedding dimension). Sample entropy and detrended fluctuation analysis (DFA) were applied to the stride time interval time series. Relative reliability was assessed using intraclass correlation coefficients and absolute reliability was determined using measurement error (ME). For both joint angles and sacrum displacement, there was a general pattern that the group average state space reconstruction method provided the highest relative reliability and lowest ME compared to the individual and test-retest average methods. The DFA exhibited good reliability, while the sample entropy showed poor reliability. The results comprise a reference material that can inspire and guide future studies of nonlinear gait dynamics.

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