Tremor affects millions of people and many patients desire alternative treatment options to medication or neural surgery. Peripheral suppression techniques are gaining greater use, but are currently applied in a trial-and-error method. To optimize these techniques, the muscles most responsible for an individual patient's tremor need to be identified. In this dissertation, I explored two parallel paths that both could aid in identifying muscles responsible for tremor. The first method utilizies measured data and a technique (coherence) that quantifies the frequency dependent correlation between two signals. Using coherence to identify muscles contributing to tremor requires at least two parts: an analysis of how tremor content is shared between muscles, and an analyis between muscle activity and joint/hand motion. The interpretation of the second analysis depends on the results of the first. The second method of identifying responsible muscles uses a mathematical model of the upper limb. With a validated model established techniques can be used to quantify the contribution to the output from each input. However, the accuracy of the model that has been previously used in the Neuromechanics Research Group had not been quantified. To evaluate the accuracy of this model, I used measured muscle activity as the input to generate simulated tremor and compared that to the measured tremor. From the first method, I found that synergistic muscles tend to share tremor content and do so in phase with each other. Therefore, tremor is likely due to a group of muscles rather than a single muscle. Additionally, I observed that the elbow flexor and wrist extensor muscles tended to be most correlated with tremor and should therefore be considered in peripheral suppression techniques. The second method revealed that while this upper-limb model shows potential to predict cases of severe tremor, improved model parameters must be identified through measurement or estimation techniques before the model should be used as it currently over-predicts the tremor.

Repeated or prolonged activation of skeletal muscle results in an acute decline in the muscle's ability to produce force, which is typically referred to as fatigue. Muscle fatigue is likely related to the by-products of cellular metabolism, alterations in neural activation and diminished membrane excitability that have been shown to accompany repeated contractions. However, the complicated etiology of the fatigue process makes it difficult to understand the relative influence of these physiological responses. Computational modeling of the skeletal muscle response to repeated activation is an appealing means of gaining insight into the mechanisms of muscle fatigue. A reasonably comprehensive model would include components that represent motor neurons and populations of muscle fibers that reflect the range of metabolic and contractile characteristics known to exist in human skeletal muscle. Consideration of joint and connective tissue mechanical properties will add translational value by predicting whole joint segment behavior that can be validated by in vivo experimentation. The proposed dissertation project involved the development of a computational model incorporating multiple components meant to represent the function of the intact neuromuscular system. The complete model combines previously-validated models of neural activation and contractile behavior with a control function that attempts to match torque output to a pre-determined task. The model uses experimentally-derived functions describing metabolic cost and force inhibition to predict the loss of force generating capacity during repeated activation. Once tested using data from a group of adult men, the parameters of this model were altered to reflect age-related changes in the human neuromuscular system. The model's ability to predict the well-established phenomenon of age-related fatigue resistance during isometric contractions was then tested. The results from this series of studies support the utility of a computational approach to the investigation of muscle fatigue, and provide useful tools for future studies.

To achieve expressive musical results in violin bowing, performers access wide ranges of combined musical tone loudness and duration variables. By comparison, allowable mechanical variability in bow stroke execution may be limited. Such constraints on string bowing variability similarly might limit variability of bowing limb movement. Constrained variability may carry risk of upper extremity musculoskeletal disorders. Therefore if musical and/or bowing-execution variables influence bowing limb movement variability, they may in turn influence risk of cumulative injury in the player. In two experimental studies we examined the influence of the musical variables of duration and sound intensity (loudness) on variability in both string bowing mechanical variables and bowing limb joint moments (i.e. rotational forces) and joint angle trajectories. Five violinists performed playing tasks in which bow strokes varied across four levels of duration and three levels of loudness. Given a constant-amplitude bow stroke, quiet, brief strokes and loud, long strokes had to be executed close to the lower and upper limits of permissible bow-on-string force (bow force). In Study #1, we computed one- and three-dimensional bow movement variance measures, in both kinematic (bow velocity across violin string, distance from bow-to-bridge) and kinetic (bow force) variables. In Study #2 we computed the cycle-to-cycle standard deviation of joint moments and angles for each moment and angular degree of freedom in the bowing limb. In each study, these variability measures were compared across the 12 experimental conditions. We hypothesized that variability would be lowest when executing quiet/brief and loud/long strokes, compared to strokes that could be executed further from bow force limits. However, it was also anticipated that variability instead could be influenced most strongly by bow and/or limb velocity, magnitude of bow force, and/or bowed-string loudness response properties. Results from both studies indicated that variability in both bow-on-string and limb movement was conditioned on these latter properties: tone duration and loudness exerted consistent effects on variances and standard deviations. Contradicting the main hypothesis, variability was not influenced by proximity to bow force limits. We conclude that bowing variability is constrained mainly by factors not specific to variability tolerance at the bow-violin string interface.

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No description available.

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Work-related musculoskeletal disorders (WMSDs) continue to present a substantial personal and economic burden. Biomarkers, in providing objective measures of physiological changes, may offer advantages over current tools for WMSD risk assessment. Existing work has identified biomarkers of cartilage and muscle damage, and demonstrated responsiveness to various forms of physical activity and biomechanical loading. Here, three studies were complete to further assess the occupational relevance/utility of three selected biomarkers: Cartilage Oligomeric Matrix Protein (COMP), Interleukin-6 (IL6), and Creatine Kinase (CK). First, the effects of age, obesity, gender, and diurnal variation was investigated. Significant effects of time, age, and gender were evident, as well as some interactive effects, for COMP and CK, but not IL6. Second, biomarker levels were compared between individuals in occupations having relatively high and low WMSD risk. IL6 levels were greater in the high-risk group, while COMP levels demonstrated an oscillatory pattern, and CK levels did not vary between groups. Third, physical demands were imposed on the lumbar spine during a repetitive flexion/extension task, under conditions with different loading and frequency. IL6 levels varied significantly over time and between added load levels, while CK levels varied over time and was influenced by load and frequency. These studies demonstrate important features of biomarkers; that personal confounding factors need to be considered, that select biomarkers may be sensitive to occupational risk factor exposure, and particularly to task parameters in lifting activities involving the lower back. Further, these studies reveal important information concerning the relevance of the selected biomarkers, favorable time points for biomarker collection, and approximate biomarker levels expected between occupations and exposure to common risk factors. These results support the use of biomarkers in occupational settings for assessing exposure and WMSD risk imposed by common risk factors. Sensitivity to exposure levels is an important precursor to risk prediction, however prospective work is needed to verify predictive validity. / Ph. D.

Farmworkers play an integral role in the production and availability of tomato fruit for consumption. Yet the work activities of farmworkers present risk factors for musculoskeletal disorders. Tasks involving stake pounding, picking, bucket toss, and trellising entail risk factors such as repetitive motions, lifting/carrying of heavy loads, and working in flexed trunk postures. These physically demanding activities are typically associated with musculoskeletal disorders (MSDs). Presently, quantitative assessments of these jobs and health risks to the workers are rare. Access to the workers who are often migrant and seasonal can pose an impediment to such investigations. This research examines three tasks performed by tomato farmworkers using objective quantitative tools such as electromyography and physical activity monitoring. It also studies the relationship between self-reported and/or clinically diagnosed chronic health conditions among tomato farmworkers in the region, and risks for developing musculoskeletal disorders in the workplace. Finally, it provides models for studying risk factors of migrant farmworkers via cooperation with a migrant health center and the construction of a tomato test plot. The results of the test plot study show that the anterior deltoid and upper trapezius muscles are disproportionately impacted by tomato farm work activity, even though the three tasks studied are of moderate physical intensity. A high prevalence of musculoskeletal pain was found to exist among tomato farmworkers with the age of the worker influencing the presence or absence of chronic and comorbid conditions. Diabetes, obesity and hypertension were studied in relation to musculoskeletal disorders. The studies described in this dissertation lay the groundwork for future studies and may also encourage policy makers to support programs and collaborative partnerships that address the needs of migrant agricultural workers. We recommend longitudinal studies to research the interplay between comorbidities, jobs performed, and musculoskeletal conditions. We also recommend the use of test plots and full-shift evaluations to better characterize the degree of overexertion in tomato industry tasks.

People with osteoarthritis (OA) suffer from joint degeneration and pain as well as difficulty performing daily activities. Joint contact forces (JCF) are important for understanding individual joint loading, however, these contact force cannot be directly measured without instrumented implants. Musculoskeletal modeling is a tool for estimating JCF without the need for surgery. The results from these models can be very different due to different approaches used in the development of a model that was used for simulation. Therefore, the first purpose of this study was to develop and validate a musculoskeletal model in which lower extremity JCF were calculated at the hip, knee, and ankle in 10 participants with hip OA (H-OA) and 10 healthy control participants using OpenSim 4.0 [simtk.org, 23]. The generic gait2392 model was scaled to participant demographics, then the inverse kinematics (IK) solution and kinetic data were input into the Residual Reduction Algorithm (RRA) to reduce modeling errors. Kinematic solutions from RRA were used in the Computed Muscle Control (CMC) tool to compute muscle forces, then JCF were estimated using the Joint Reaction Analysis tool. Validation included JCF comparisons to published data of similar participant samples during level walking, and movement simulation quality was assessed with residual forces and moments applied at the pelvis, joint reserve actuators, and kinematic tracking errors. The computed JCFs were similar to the overall trends of published JCF results from similar participant samples, however the values of the computed JCFs were anywhere from 0.5 times body weight (BW) to 3BW larger than those in published studies. Simulation quality assessment resulted in low residual forces and moments, and low tracking errors. Most of the reserve actuators were small as well, besides pelvis rotation and hip rotation. The computed JCF were then used in the second portion of this study to determine the effect of group and side on JCF during both the weight acceptance and push-off phases of level walking. It was determined that there was a significant difference in the knee and ankle JCF during the weight acceptance portion of stance phase and at all joints during the push-off phase when comparing the H-OA and control groups on the affected limb. A significant interaction between group and limb was found for the peak hip JCF timing (% stance) during the push-off portion of the stance phase (p=0.009). These results demonstrate that H-OA participants experience an earlier peak hip JCF during propulsion on their affected limb. Based on previous research in OA that has examined spatiotemporal measures, this finding suggests that H-OA participants may use step or stride length changes as a strategy to decrease or limit pain and loading on the affected limb. Knowledge of potential JCF differences in H-OA participants, such as timing of the peaks in either portion of the stance phase, could provide useful insight to clinicians and therapists to make decisions on how to proceed with treatment or rehabilitation programs. / Master of Science / People with osteoarthritis suffer from joint degeneration and pain as well as difficulty performing daily activities, like walking. It is important to understand the forces and loading within individual joints. Musculoskeletal modeling is one way that researchers can estimate these joint contact forces (JCF) without needing a joint replacement implant that can measure these forces. When it comes to modeling simulations, there is a wide variety of results. Therefore, the first purpose of this study was to develop and validate a musculoskeletal model in which JCFs were calculated at the hip, knee, and ankle in 10 participants with hip osteoarthritis and 10 healthy adults. Validation of the model was completed through a comparison between computed results and published data of similar participant samples during level walking. The computed results were similar to the overall trends of published JCF results, however the numerical values themselves were larger than those in published studies. The computed JCFs were then used in the second portion of this study to determine how the two groups and limbs differ during level walking. There was a significant difference in the knee and ankle JCF during the first half of the stance phase and in all joints during the second half of stance when comparing the two groups. The hip osteoarthritis participants also experience an earlier peak hip JCF during the second half of stance phase on their affected limb. This finding suggests that hip osteoarthritis participants may change the way they take a step as a strategy to decrease or limit pain and loading on the affected limb. Knowledge of potential JCF differences, such as timing of the peaks in either portion of the stance phase, could provide useful insight to clinicians and therapists to make decisions on how to proceed with treatment or rehabilitation programs.

Objectives: This study aimed to investigate the risks and impacts associated with fractures, osteoporosis, frailty, physical function, and dementia in older adults in community and LTC setting. The study aims to identify important factors influencing these health issues and identify strategies for improving management and outcomes. Methods: The research integrates data from three primary sources: Project 1 (ICES Data Repository): Healthcare utilization and administrative databases were linked using unique, encoded identifiers from the ICES Data Repository to estimate hip fractures and osteoporosis management among adults aged 66 and older from April 1, 2014, to March 31, 2018. Osteoporosis management was assessed through pharmacotherapy records. Sex-specific and age-standardized rates were compared based on pre-fracture residency and discharge location (e.g., LTC to LTC, community to LTC, or community to community). Fracture risk was determined using the Fracture Risk Scale (FRS). Project 2 (Canadian Longitudinal Study on Aging - CLSA): Participants aged 45 to 85 years who completed both the baseline and three-year follow-up assessments were included. Outcomes examined include frailty (Fried Frailty Phenotype), and physical function limitations. MSK conditions were self-reported diagnosis by a health care professional and included rheumatoid arthritis (RA), osteoarthritis (OA), low-back pain, osteoporosis, and related fractures. Project 3: The review employed Arksey and O'Malley's framework, guided by Joanna Briggs Institute methodology and PRISMA-ScR guidelines. A comprehensive search strategy was implemented across MEDLINE, EMBASE, CINAHL, and grey literature. Independent reviewers used Covidence software for study selection and data extraction. A narrative synthesis was conducted to summarize findings, identify patterns, and highlight gaps in the literature. Findings: We found increasing hip fracture rates and low osteoporosis treatment in LTC settings, highlighting to the need for improved screening and management of osteoporosis treatment in LTC. In community, hip fracture rates decreased. We found that older adults with musculoskeletal (MSK) conditions at baseline were more likely to experience frailty at the three-year follow-up compared to those without MSK conditions. However, this association was not significant in the unadjusted analysis. Individuals with cognitive decline experience worse outcomes following hip fractures, underscoring the need for integrated care addressing both physical and cognitive health. Conclusion: Hip fractures, frailty, physical function decline, and cognitive decline are prevalent and interrelated issues among older adults aged 65 and older. These findings underscore the need for improved screening and integrated care strategies to enhance management and prevention of these complex health challenges. / Thesis / Doctor of Philosophy (PhD) / Aging is associated with increased risks of osteoporosis, fractures, frailty, physical function decline, and dementia, particularly for older adults in long-term care (LTC). This study explores these health challenges by analyzing data from three key sources: ICES, the Canadian Longitudinal Study on Aging (CLSA), and a scoping review of patient-important outcomes following a hip fracture in older adults with cognitive impairment or dementia. First, we found increasing hip fracture rates in LTC and among older adults living in community at time of fracture and transferred to LTC post fracture. Osteoporosis treatment was low among high fracture risk LTC residents. Second, we found that older adults with baseline musculoskeletal (MSK) conditions (osteoporosis, fractures, osteoarthritis (OA), rheumatoid arthritis, and back pain) were more likely to become frail and have physical function limitation over three years compared to those without MSK conditions. However, after adjusting for covariates, these associations were no longer significant. Among the individual MSK conditions, we found older adults with only OA and osteoporosis-related fractures to be significantly associated with physical functional limitations. Lastly, we found that following a hip fracture, older adults with cognitive impairment or dementia have poorer functional outcomes, reduced quality of life, higher hospitalization and mortality rates, and are significantly more likely to be institutionalized compared to older adults without cognitive impairment or dementia, highlighting the need for integrated care that addresses both physical and cognitive health