Department of Exercise, Sport and Lifestyle Medicine

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Browsing Department of Exercise, Sport and Lifestyle Medicine by Subject "Accelerometers"

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    Analyzing gait parameters in trail runners using wireless trunk accelerometry during real-world and treadmill incline running
    (Stellenbosch : Stellenbosch University, 2020-12) Bergh, Oloff Charles Wessel; Venter, Ranel; De Waal, Simon Jake; Faculty of Medicine and Health Sciences. Dept. of Sport Science.
    ENGLISH ABSTRACT: Few studies have explored dynamic stability when running over complex or challenging surfaces, and no studies have investigated how trail terrain could affect components of dynamic stability. The aim of this study was to measure the acute changes in dynamic stability when running at incline, between treadmill and trail surfaces. Twelve recreational trail runners (age 25.2 ±2.6 years; mass 78.8 ±5.9 kg; height 183.6 ±7.1 cm) participated and completed all aspects of testing. They ran at 10 km.h-1with an eight-degree incline, over both treadmill and trail surfaces. Each participant had a single Noraxon®myoMotion Research PRO inertial measurement unit (IMU) attached to their third lumbar vertebrae region, capable of collecting wireless acceleration data. Linear acceleration data was captured up to 200 Hz and ± 16 g at the trunk region in three-dimensions, namely the vertical (VT), anterior-posterior (AP) and mediolateral (ML). Data was streamed to the Noraxon®myo RESEARCH software. Thereafter, the data was filtered using a zero-lag 4thorder low-pass Butterworth filter with a cut-off frequency of 50 Hz. Filtered acceleration data was imported into MATLAB R2020a (Version 9.6), with a custom written code performing an autocorrelation procedure of each participant over both treadmill and trail surfaces. The autocorrelations provided information regarding the step and stride regularity, as well as the symmetry of the individual over the two terrains, based on the three-dimensional accelerations at the trunk. Furthermore, mean step and stride times, as well as their coefficients of variations (CV) were calculated from the filtered data. Results were reported in the article (Chapter Four) and indicated that step and stride regularity was decreased (p< 0.01) in all three-dimensions when running over the more complex trail surface, compared to the steady treadmill surface. The AP and ML directions indicated a greater degree of diminution compared to the VT and is evident in the symmetry values. Symmetry decreased over the trail surface for both the AP (z= -3.06, p< 0.01) and ML (p< 0.01) directions, but not in the VT (z= -1.65, p= 0.10) direction. Additionally, there was no change in mean step (p= 0.45) and stride (p= 0.33) times, but a significant increase was observed for both step CV (p< 0.01) and stride CV (p< 0.01) when running on the trail surface. The first null hypothesis was rejected, as the coefficients of variation for both step and stride times indicated a significant difference when comparing the treadmill and trail surfaces. The second null hypothesis was rejected, as the trail surface did indicate a general decrease in dynamic stability components compared to the treadmill. In conclusion the trail demonstrated a higher degree of step and stride variability, and low symmetry, primarily due to the inconsistent nature of the trail surface. Future studies could investigate the role of cognition during trail running, by examining the decision-making process while traversing complex terrain such as the trail environment. Furthermore, future studies in the field of sports biomechanics could aim to incorporate a greater degree of software technology, such as adopting a more algorithmic approach to analysing data.