Browsing by Author "Bergh, Oloff Charles Wessel"

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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.
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    The Influence of neck muscle characteristics on head kinematics during lateral impacts : a simulation based analysis
    (2023-03) Bergh, Oloff Charles Wessel; Van der Merwe, Johan; De Jongh, Cornel; Derman, Wayne; Stellenbosch University. Faculty of Engineering. Institute of Biomedical Engineering.
    ENGLISH SUMMARY: The skull contains the most critical component of the human body, the brain. Large changes in the velocity and acceleration of the skull, specifically in an angular manner, have been associated with an increased risk of concussion or mild traumatic brain injuries. Modifiable risk factors can be defined as intrinsic characteristics that can be altered to decrease the risk of head injury. Previous studies have investigated neck muscle strength as a potential modifiable risk factor in sports research. However, literature appears to be divided regarding the influence of neck muscle strength on head kinematics and injury risk. Additionally, research associated with individuals who demonstrate a decline in neck muscle strength compared to control subjects appears to be scarce, potentially due to ethical concerns. This project aims to contribute to current literature and evaluate the influence of neck muscle characteristics, such as the maximum isometric and eccentric strength, on the kinematics of the skull during laterally induced head collisions through a simulation-based approach. Multibody dynamic computer models were used to determine the influence of neck muscle characteristics on head kinematics and subsequent head injury risks. The models were based on the original Hyoid model in OpenSim by Mortensen, Vasavada and Merryweather (2018), which has been verified and validated against experimental responses with similar total neck muscle strength values. The Normal model in this project demonstrated the same muscle characteristics as the original Hyoid model. The two stronger models, referred to as the Intermediate and Max models, have increases in maximum isometric and eccentric muscle strength compared to the Normal model. The Intermediate model has realistic achievable neck muscle characteristics of an individual who has undergone specific neck training, while the Max model represents a highly trained athlete with significantly strengthened neck musculature. The Decreased model has lower total neck muscle strength compared to the Normal model and is based on the reductions in muscle characteristics of elderly individuals. The static optimization tool within the OpenSim environment was used to determine the optimal muscular activations of the different models. These activations were subsequently used in the forward dynamic tool to determine the influence of the neck muscle characteristics on head kinematics during increasing lateral impacts. The head kinematics were then used to calculate the head injury criterion (HIC15), a commonly used metric to determine the extent of head injuries based on empirical data. The stronger models consistently showed lower head kinematic and HIC15 values compared to the Normal model, while the Decreased model always demonstrated higher kinematics with a greater risk of injury. At a low external force there was a considerable influence of the neck muscle characteristics on head kinematics and injury risk. However, a non-linear trend indicated that the influence of the neck muscles declined as the external force increased. This could indicate that the influence of the neck muscle characteristics might be overshadowed by large external forces, but could still play a role in reducing head kinematics and injury-risk at lower forces.