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.

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.

No description available.

No description available.

No description available.

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.

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.

Yes / Integrated models of care intend to provide seamless and timely access to health and social care services. This study investigated the integration of musculoskeletal services across community and secondary care boundaries, including the introduction of a single point of access from which patients were triaged. Staff (n = 15) involved in service development and delivery were interviewed about how, why and to what extent integration impacted service delivery. The analysis focused on staff experiences of using an on-line patient self-referral form and co-located clinics to enhance decision-making in triage, and on the provision of educational materials and de-medicalising language in patient consultations to support self-management. Single point of access, including online self-referral, were operationalised during data collection, but co-located clinics were not. Triage staff explained that the volume of referrals and quality of information provided in online self-referrals sometimes constrained decision-making in triage. Secondary care staff discussed concerns that the single point of access might not consistently identify patients with hard to diagnose conditions that require timely surgical intervention. This concern appeared to constrain staff engagement with integration, potentially inhibiting the delivery of co-located clinics. However, triage staff accessed support to inform secondary care referral via alternate modes. Patient circumstances, for example, need for reassurance, necessitated multiple self-management strategies and innovative approaches were developed to provide patients ongoing and professionally led support. Findings emphasise that restructuring services requires engagement from diverse stakeholders. Collaborating with stakeholders to address their concerns about the impact of restructures on well-established pathways may help cultivate this engagement. / Newcastle upon Tyne Hospitals NHS Foundation Trust