The application of PCA as a movement pattern recognition technique: A proof of principle

Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.

Investigating the Association Between Computer-Mediated Communication (CMC) and the Health of Canadian Young People: A Mixed Methods Study

Canadian young people are increasingly more connected through technological devices. This computer-mediated communication (CMC) can result in heightened connection and social support but can also lead to inadequate personal and physical connections. As technology evolves, its influence on health and well-being is important to investigate, especially among youth. This study aims to investigate the potential influences of computer-mediated communication (CMC) on the health of Canadian youth, using both quantitative and qualitative research approaches. This mixed-methods study utilized data from the 2013-2014 Health Behaviour in School-aged Children survey for Canada (n=30,117) and focus group data involving Ontario youth (7 groups involving 40 youth). In the quantitative component, a random-effects multilevel Poisson regression was employed to identify the effects of CMC on loneliness, stratified to explore interaction with family communication quality. A qualitative, inductive content analysis was applied to the focus group transcripts using a grounded theory inspired methodology. Through open line-by-line coding followed by axial coding, main categories and themes were identified. The quality of family communication modified the association between CMC use and loneliness. Among youth experiencing the highest quartile of family communication, daily use of verbal and social media CMC was significantly associated with reports of loneliness. The qualitative analysis revealed two overarching concepts that: (1) the health impacts of CMC are multidimensional and (2) there exists a duality of both positive and negative influences of CMC on health. Four themes were identified within this framework: (1) physical activity, (2) mental and emotional disturbance, (3) mindfulness, and (4) relationships. Overall, there is a high proportion of loneliness among Canadian youth, but this is not uniform for all. The associations between CMC and health are influenced by external and contextual factors, including family communication quality. Further, the technologically rich world in which young people live has a diverse impact on their health. For youth, their relationships with others and the context of CMC use shape overall influences on their health.

The relationship of E. coli and total coliform culture to the quantitative molecular detection of various fecal indicators, sources, and pathogens in private drinking water wells

Water remains a predominant vector for human enteric pathogens not just for developing countries but also developed nations, where numerous infectious disease outbreaks, linked to the contamination of drinking water have been documented. Private drinking water wells are a source of drinking water that is largely unstudied even though a significant percentage of the population in Ontario relies on wells as their primary water source. As there exists little to no systematic surveillance for enteric infections or outbreaks related to well water sources, these individuals may be at higher risk of waterborne infectious diseases. The relationships between various fecal indicators in the water of private drinking water wells, including E. coli, Total Coliforms (TC) and Bacteroides, and enteric pathogens, including Campylobacter jejuni, Salmonella spp., and Shiga toxin producing E. coli, were studied. Convenience private well water samples collected from various regions of interest during the summer of 2014 underwent membrane filtration and culture to determine quantities of E. coli and TC colony forming units. 289 E. coli positive and 230 TC-only waters were successfully analyzed by individual qPCR assays for the aforementioned enteric pathogens. Microbial source tracking methods targeted to specific Bacteroides were used to determine the source of fecal contamination as either human or bovine. The source of fecal contamination varied by geographic region and is thought to be due to such things as differences in septic tank density and underlying geology, among others. Fecal indicators, E. coli and Bacteroides, were significantly correlated. E. coli as measured by qPCR was more strongly correlated to both total and human-specific Bacteroides genetic markers than culturable E. coli. Lastly, 1.9% of samples showed molecular evidence of contamination with enteric pathogens. Although low, this finding is significant given the limited volume of water available for testing, and suggests a potential health risk to consumers. Knowing the extent of contamination, as well as the biologic source, can better inform risk assessment and the development of potential intervention strategies for private well water in specific regions of Ontario.