Improved Accuracy in Optical Motion Capture Measurements Leads to Increased Sensitivity to Kinematic Changes

Clinical optical motion capture allows us to obtain kinematic and kinetic outcome measures that aid clinicians in diagnosing and treating different pathologies affecting healthy gait. The long term aim for gait centres is for subject-specific analyses that can predict, prevent, or reverse the effects of pathologies through gait retraining. To track the body, anatomical segment coordinate systems are commonly created by applying markers to the surface of the skin over specific, bony anatomy that is manually palpated. The location and placement of these markers is subjective and precision errors of up to 25mm have been reported [1]. Additionally, the selection of which anatomical landmarks to use in segment models can result in large angular differences; for example angular differences in the trunk can range up to 53o for the same motion depending on marker placement [2]. These errors can result in erroneous kinematic outcomes that either diminish or increase the apparent effects of a treatment or pathology compared to healthy data. Our goal was to improve the accuracy and precision of optical motion capture outcome measures. This thesis describes two separate studies. In the first study we aimed to establish an approach that would allow us to independently quantify the error among trunk models. Using this approach we determined if there was a best model to accurately track trunk motion. In the second study we designed a device to improve precision for test, re-test protocols that would also reduce the set-up time for motion capture experiments. Our method to compare a kinematically derived centre of mass velocity to one that was derived kinetically was successful in quantifying error among trunk models. Our findings indicate that models that use lateral shoulder markers as well as limit the translational degrees of freedom of the trunk through shared pelvic markers result in the least amount of error for the tasks we studied. We also successfully reduced intra- and inter-operator anatomical marker placement errors using a marker alignment device. The improved accuracy and precision resulting from the methods established in this thesis may lead to increased sensitivity to changes in kinematics, and ultimately result in more consistent treatment outcomes.

The relationship between changes in cardiovascular function and changes in VO2peak following SIT

Background: It is well known that sprint interval training (SIT), induces significant increases in peak oxygen uptake (VO2peak) at the group level. However, there have been only a few studies that have addressed the variability of VO2peak response following SIT, and precise mechanism(s) that may explain individual magnitude of response are unknown. Purpose: Therefore, the purpose of this thesis was to: 1) examine the inter-individual variability of the VO2peak response following SIT, 2) to inspect the relationship between changes in both central and peripheral measures and changes in VO2peak, and 3) to assess if peripheral or central adaptations play a role in whether an individual is a high or low responder with respect to VO2peak. Subjects: Twenty-two young, recreationally active males (age: 20.4 1.7 years; weight: 78.4 10.2 kg; VO2peak: 3.7 0.62 L/min) Methods: VO2peak (L/min), peak cardiac output (Qpeak [L/min]), and peak deoxygenated hemoglobin (HHbpeak [mM]) were measured before and after 16 sessions of SIT (Tabata Protocol) over four weeks. Peak a-vO2diff was calculated using a derivation of the Fick equation. Results: Due to a systematic error, HHbpeak could not be used to differentiate between individual responses. There was a large range of VO2peak response from pre to post testing (-4.75 to 32.18% change) and there was a significant difference between the Low Response Group (LRG) (n=8) and the High Response Group (HRG) (n=8) [f(1, 14)= 64.27, p<0.001]. Furthermore, there was no correlation between delta () VO2peak and Qpeak (r=-0.18, p=0.46) for all participants, nor was there an interaction effect between the Low and High Response Groups [f(1,11)=0.572, p=0.47]. Lastly, there was a significant correlation between VO2peak and peak a-vO2diff [r=0.692, p<0.001], and a significant interaction effect with peak a-vO2diff [f(1, 14)= 13.27, p<0.004] when comparing the HRG to the LRG. Conclusions: There was inter-individual variability of VO2peak response following 4 weeks of SIT, but central adaptations did not influence this variation. This suggests that peripheral adaptations may be responsible for VO2peak adaptation.