Locomotor variability is inherent to movement and, in healthy systems, contains a predictable structure. In this study, detrended fluctuation analysis (DFA) was used to quantify the structure of variability in locomotion. Using DFA, long-range correlations (α) are calculated in over ground running and the influence of injury and fatigue on α is examined. An accelerometer was mounted to the tibia of 18 runners (9 with a history of injury) to quantify stride time. Participants ran at their preferred 5k pace±5% on an indoor track to fatigue. The complete time series data were divided into three consecutive intervals (beginning, middle, and end). Mean, standard deviation (SD), coefficient of variation (CV) and α of stride times were calculated for each interval. Averages for all variables were calculated per group for statistical analysis. No significant interval, group or interval×group effects were found for mean, SD or CV of stride time. A significant linear trend in α for interval occurred with a reduction in α over the course of the run (p=0.01) indicating that over the run, stride times of runners became more unpredictable. This was likely due to movement errors associated with fatigue necessitating frequent corrections. The injured group exhibited lower α (M=0.79, CI(95)=0.70, 0.88) than the non-injured group (p=0.01) (M=0.96, CI(95)=0.88, 1.05); a reduction hypothesized to be associated with altered complexity. Overall, these findings suggest injury and fatigue influence neuromuscular output during running.
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http://dx.doi.org/10.1016/j.gaitpost.2010.09.020 | DOI Listing |
Sensors (Basel)
January 2025
Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.
Portable monitoring devices based on Inertial Measurement Units (IMUs) have the potential to serve as quantitative assessments of human movement. This article proposes a new method to identify the optimal placements of the IMUs and quantify the smoothness of the gait. First, it identifies gait events: foot-strike (FS) and foot-off (FO).
View Article and Find Full Text PDFSensors (Basel)
January 2025
German Center for Vertigo and Balance Disorders (DSGZ), LMU University Hospital, LMU Munich, 81377 Munich, Germany.
Instrumented gait analysis is widely used in clinical settings for the early detection of neurological disorders, monitoring disease progression, and evaluating fall risk. However, the gold-standard marker-based 3D motion analysis is limited by high time and personnel demands. Advances in computer vision now enable markerless whole-body tracking with high accuracy.
View Article and Find Full Text PDFHealthcare (Basel)
January 2025
Department of Physical Therapy, Daejeon Health University, Daejeon 30711, Republic of Korea.
Background: Virtual reality-based training has been widely used for post-stroke patients due to its positive effects on functional aspects by promoting brain plasticity.
Objective: This study aimed to investigate the effectiveness of gait training with virtual reality-based real-time feedback on motor function, balance, and spatiotemporal gait parameters in post-stroke patients.
Methods: Fifteen patients ( = 15) with chronic stroke were randomly assigned to either the virtual reality-based real-time feedback with treadmill gait training (experimental group = 8) or the treadmill gait training (control group = 7).
Neurol Int
January 2025
Laboratório de Marcha, Centro de Medicina de Reabilitação de Alcoitão, 2649-506 Alcabideche, Portugal.
Background/objectives: Post-stroke hemiparetic gait often presents with asymmetric patterns to compensate for stability deficits. This study examines gait differences in chronic stroke patients with spastic hemiparesis based on initial foot contact type-forefoot versus rearfoot.
Methods: Thirty-four independently walking spastic hemiparetic patients were retrospectively analyzed.
PLoS One
January 2025
Department of Kinesiology and Sport Sciences, University of Miami, Coral Gables, FL, United States of America.
The KinaTrax markerless motion capture system, used extensively in the analysis of baseball pitching and hitting, is currently being adapted for use in clinical biomechanics. In clinical and laboratory environments, repeatability is inherent to the quality of any diagnostic tool. The KinaTrax system was assessed on within- and between-session reliability for gait kinematic and spatiotemporal parameters in healthy adults.
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