Browsing by Author "Bertram, John E. A."
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- ItemOpen AccessDiscovering the importance of loading rate on articular cartilage: using low magnitude, high frequency dynamic compression to identify the time-dependent behaviors of articular cartilage(2009) Szarko, Matthew J.; Bertram, John E. A.
- ItemOpen AccessFreeze-thaw treatment effects on the dynamic mechanical properties of articular cartilage(BioMed Central, 2010-10-08) Szarko, Matthew; Muldrew, Ken; Bertram, John E. A.
- ItemOpen AccessFrom molecules to muscles: equine digital flexor muscle contractile physiology and function(2006) Butcher, Michael T.; Syme, Douglas A.; Bertram, John E. A.
- ItemOpen AccessGait Entrainment in Coupled Oscillator Systems: Clarifying the Role of Energy Optimization in Human Walking(2020-01-13) Schroeder, Ryan T.; Bertram, John E. A.; Croft, James L.; Sawicki, Gregory S.; von Tscharner, Vinzenz; Shrive, Nigel; Cluff, Tyler; Rubenson, JonasEmpirical evidence suggests that parameters of human gait (e.g. step frequency, step length) tend to minimize energy expenditure. However, it is unclear if individuals can adapt to dynamic environments in real time, i.e. continuously optimize energy expenditure, and to what extent. Two coupled oscillator systems were used to test the learned interactions of individuals within dynamic environments: (1) experienced farmworkers carrying oscillating loads on a flexible bamboo pole and (2) individuals walking on a treadmill while strapped to a mechatronics oscillator system providing periodic forces to the body. Reductionist trajectory optimization models predicted energy-minimizing gait interactions within the coupled oscillator systems and were compared to experimental data assessed with linear mixed models. On average, pole carriers significantly adjusted step frequency by 3.3% (0.067 Hz, p=0.014) to accommodate the bamboo pole – consistent with model predictions of energy savings. Novice subjects entrained (i.e. synchronized) their step frequency with machine oscillations up to ±10% of preferred step frequency and at amplitudes as low as 5% body weight (or ~33 N). Still, some subjects rarely entrained at all, and many exhibited transient entrainment, i.e. they drifted in and out of step frequencies matching the machine oscillations. Overall, subject entrainment was more robust and consistent with lower frequencies and higher amplitudes (20-30% of body weight). Although no systematic difference was found between the metabolic consumption of subjects during and not during entrainment, the net mechanical work done on subjects by the force oscillations had a strong effect on metabolic output (p<0.0001). Net work was largely determined by the alignment of oscillation forces within the gait cycle. Both the optimization model and subjects aligned force oscillations with their body velocity to increase positive power. All in all, it seems that subjects prefer entrainment with environmental oscillations under certain circumstances. However, entrainment does not appear to be motivated by energetic cost, at least not directly and not as a first priority. It is possible that individuals stabilize interactions with the environment (e.g. entrainment) as a prerequisite for effective feedforward and/or feedback gait control.
- ItemOpen AccessHuman hopping: a model for understanding the mechanics and energetics of bouncing gaits(2011) Gutmann, Anne Katharine; Bertram, John E. A.
- ItemOpen AccessOptimality, Objectives, and Trade-Offs in Motor Control under Uncertainty(2023-09-22) Ryu, Hansol; Bertram, John E. A.; Srinivasan, Manoj; Whelan, Patrick; Sternad, Dagmar; Cone, JacksonBiological motor control involves multiple objectives and constraints. In this thesis, I investigated the influence of uncertainty on biological sensorimotor control and decision-making, considering various objectives. In the first study, I used a simple biped walking model simulation to study the control of a rhythmic movement under uncertainty. Uncertainty necessitates a more sophisticated form of motor control involving internal model and sensing, and their effective integration. The optimality of the neural pattern generator incorporating sensory information was shown to be dependent on the relative amount of physical disturbance and sensor noise. When the controller was optimized for state estimation, other objectives of improved energy efficiency, reduced variability, and reduced number of falls were also satisfied. In the second study, human participants performed regression and classification tasks on visually presented scatterplot data. The tasks involved a trade-off between acting on small but prevalent errors and acting on big but scarce errors. We used inverse optimization to characterize the loss function used by humans in these regression and classification tasks, and found that these loss functions change systematically as the data sparsity changed. Despite being highly variable, there were overall shifts towards compensating for prevalent small errors more when the sparsity of the visual data decreased. In the third study, I extended the pattern recognition tasks to include visually mediated force tracking. When participants tracked force targets with visual noise, we observed a slight yet consistent force tracking bias. This bias, which increased with noise, was not explained by commonly hypothesized objectives such as a tendency to reduce effort while regulating error. Additional experiments revealed that a model balancing error reduction and transition reduction tendencies effectively explained and predicted experimental data. Transition reduction tendency was further separated into recency bias and central tendency bias. Notably, this bias disappeared when the task became purely visual, suggesting that such biases could be task-dependent. These findings across the three studies provide useful insights into understanding how uncertainty changes objectives and their trade-offs in biological motor control, and in turn, results in a different control strategy and behaviors.
- ItemOpen AccessSelected Methodological Approaches to Identify Functional Groups in Running(2017-12-21) Hoerzer, Stefan; Nigg, Benno M.; Edwards, William Brent; Stefanyshyn, Darren J; Von Tscharner, Vinzenz; Bertram, John E. A.; Brüggemann, Gert-PeterA footwear construction typically produces different biomechanical, physiological, and/or perceptual responses for different groups of individuals. Consequently, a given insert or shoe can be beneficial for one group, but ineffective or even detrimental for another group. This observation represents a key challenge in the attempt to develop athletic footwear constructions that improve athletic performance, reduce the risk of movement-related injuries, and/or enhance comfort. A functional group is a collection of individuals with the same functional solutions when executing a locomotion task, and when reacting to a locomotion task intervention, such as footwear. It was speculated that tailoring footwear constructions to the functional solutions of these groups might help to develop footwear that promotes comfort, health, and/or performance. Before footwear constructions can be matched to functional groups, the groups have to be identified. To date, however, no systematic methodological approach exists to identify functional groups. Therefore, the main objective of this doctoral thesis was to develop and test methodological approaches that lead to the identification of functional groups in running. The first approach applied pattern recognition techniques to running kinematics in order to identify functional groups. The second approach combined footwear comfort with kinematic and muscle activity data collected during running to identify functional groups. The results showed that both tested approaches successfully identified functional groups. The main finding of this thesis is therefore that functional groups can be identified (1) by utilizing pattern recognition techniques, and (2) by isolating individuals who choose the same footwear as comfortable and excluding all individuals from this groups who do not share the same biomechanical solutions. Therefore, this PhD research provides a set of tools that can be utilized to identify functional groups in order to gain a better understanding about their specific functional solutions, biological characteristics, and footwear requirements.