<p>Current stabilization methods for periprosthetic fractures of the distal femur have been inadequate in achieving sufficient fixation and can lead to complications rates as high as 29%. Therefore, the overall objective of this study was to design, manufacture and evaluate (experimentally and computationally) a novel plating method for improving the treatment of periprosthetic fractures of the distal femur.</p> <p>Medial and lateral prototype plates were designed and manufactured based on the geometry of a synthetic femur and a femoral prosthesis. The two plates were linked via a compression screw and a small tab on each plate that inserts into pre-existing slots on the prosthesis to enhance rigidity of the construct. Synthetic femurs were used to assess the ability of the prototype plates to stabilize a periprosthetic fracture compared to a traditional single lateral plate. Each femur was subjected to a testing protocol that involved compressive and bending loading of the sample. The relative motion between the distal and proximal fragments during loading was then measured using both 2D and 3D motion tracking techniques. Both techniques revealed that the prototype bilateral plates were able to reduce motion of the fracture site compared to a single lateral plate.</p> <p>The final objective concerned the development of a finite element model to represent the experimental testing. The fracture gap motion obtained from the final model did not completely agree with the experimental data; however, additional experimental measurements found that the majority of these differences could be attributed to simplification made at the tab-slot interaction. Despite the difference, the model represents a significant step forward in the simulation of periprosthetic fracture treatment, and further refinement would allow for optimization of the plate design.</p> <p>Overall, the results of this thesis indicate that an alternative approach to treating periprosthetic fractures exists that is capable of improving fracture stabilization.</p> / Master of Applied Science (MASc)

<p>Microinjection is an established and reliable method to deliver transgenic constructs and other reagents to specific locations in the animal. Specifically, microinjection of a desired DNA construct into the distal gonad is the most widely used method to generate germ-line transformation of <em>C. elegans</em>. Although, current <em>C. elegans</em> microinjection method is an effective manner for creating transgenic worms, it requirements such as expensive multi DOF micromanipulator, detailed injection alignment procedure and skilled operator which makes the microinjection process slow and not suitable for scale to high throughput. Although many microfabricated microinjectors exist, none of them are capable of immobilizing a freely mobile animal such as <em>C.elegans</em> worm. In this research, a microfluidic microinjector was developed to simultaneously immobilize a freely mobile animal such as <em>C.elegans</em> and perform microinjection by using a simple and fast mechanism for needle actuation. The entire process of the microinjection takes ~30 seconds which includes 10s for worm loading and aligning, 5s needle penetration, 5s reagent injection and 5s worm unloading. The capability of the microinjector chip for creating transgenic <em>C. elegans</em> was illustrated (with success rate between 4% to 20%)</p> / Master of Science (MSc)

This thesis presents an impedance control strategy for a novel powered hip exoskeleton designed to provide partial assistance and leverage the dynamics of human gait. The control strategy is based on impedance control and provides the user assistance as needed which is determined by the user’s interaction with the exoskeleton. A series elastic element is used to drive the exoskeleton and measures the interaction torque between the user and the device. The device operates in two modes. Free mode is a low impedance state that attempts to provide no assistance. Assist mode increases the gains of the controller to provide assistance as needed. The device was tested on five healthy subjects, and the resulting assistive hip torque was evaluated to determine the ability of the controller to provide gait assistance. The device was evaluated at different speeds to assess the gait speed adaptation performance of the controller. Results show that hip torque assistance range was between 0.3 to 0.5 Nm/kg across the subjects, corresponding to 24% to 40% of the maximum hip torque requirements of healthy adults during walking. The peak power provided by the system is 35 W on average and a peak power of up to 45 W.

The product of this thesis aims to enable the study of the biochemical and physical dynamics of the lower limbs at high levels of muscle tension and fast contraction speeds. This is accomplished in part by a magnetic resonance (MR) compatible ergometer designed to apply a load as a torque of up to 420 Nm acting against knee extension at speeds as high as 4.7 rad/s. The system can also be adapted to apply the load as a force of up to 1200 N acting against full leg extension. The ergometer is designed to enable the use of magnetic resonance spectroscopy and imaging in a three Tesla Siemens Skyra MRI system. Due to the electromagnetic limitations of having the device operate inside the magnet, the design is split into two components. One designed to fit inside the 70 cm bore of the scanner. This component is electromagnetically passive; made out of materials exhibiting minimal magnetic interference, and having no electrically powered parts. The other component is electromagnetically active; it contains all of the powered elements and actuates the passive part from another room. A tensioned cable transmits power through a waveguide; a pipe through the wall of the MRI room with an RF shield. The device was tested applying a sagittal plane moment on the knee joint during isometric, isokinetic, isotonic, and constant power contractions.

<p dir="ltr">Microfluidic techniques have been widely adopted in biomedical research due to the pre- cise control of fluids, small volume requirement, low cost and etc, and have boosted the development of biomolecular interaction analysis, point-of-care diagnostics, and biosensors.</p><p dir="ltr">Protein-protein interaction plays a key role in biological, biomedical and pharmaceutical research. The technical development of biosensors, new drugs and vaccines, and disease diagnostics heavily rely on the characterization of protein-protein interaction kinetics. The current gold standard assays for measuring protein-protein interaction are surface plasmon resonance (SPR), and bio-layer interferometry (BLI). These commercial devices are accurate but expensive, however.</p><p dir="ltr">Here, I have developed new microfluidic techniques and models in protein-protein in- teraction kinetics measurement, rotational diffusion coefficient modeling, electrochemical impedance spectroscopy-based biosensors, and two-phase porous media flow models. Firstly, I applied particle diffusometry (PD) in the streptavidin-biotin binding kinetics measurement, utilizing a Y-junction microchannel. Secondly, to reduce solution volumes used in an analysis experiment, I designed a low-volume chip and coupled it with PD to measure the binding kinetics of human immunodeficiency virus p24 antibody-antigen interactions. Thirdly, con- sidering the Brownian motion of the non-symmetric particles, I developed a new model to efficiently compute particles’ rotational diffusion coefficients. Fourthly, to make economic biosensors to detect multiple biomarkers, I created a new chip, enabling hundreds of tests in a single droplet (∼ 50 μL) on one chip. Finally, to understand the liquid flow in porous media, such as nitrocellulose in lateral flow assays, I built a new two-phase porous media flow model based on the Navier-Stokes equation and compared it with experiments. These techniques and models underwent rigorous experimental and computational validation, demonstrating their effectiveness and performance.</p>

Stroke is a leading cause of long-term disability, affecting thousands of individuals annually and significantly impairing their mobility, independence, and quality of life. Traditional methods for assessing motor impairments are often costly and invasive, creating substantial barriers to effective rehabilitation. This thesis explores the use of DeepLabCut (DLC), a deep-learning-based pose estimation tool, to extract clinically meaningful kinematic features from video data of stroke survivors with upper-extremity (UE) impairments. To conduct this investigation, a specialized protocol was developed to tailor DLC for analyzing movements characteristic of UE impairments in stroke survivors. This protocol was validated through comparative analysis using peak acceleration (PA), mean squared jerk (MSJ), and area under the curve (AUC) as kinematic features. These features were extracted from the DLC output and compared to those derived from the assumed ground-truth data from IMU sensors worn by the participants. The accuracy of this analysis was quantified using percent mean squared error (PMSE) between each IMU sensor and DLC. PMSE analysis indicates that DLC-based kinematic features capture aspects of both accelerometer and gyroscope for the control participant. PA (8.78%) and AUC (3.28%) align more closely with the gyroscope, while MSJ (5.20%) demonstrates greater agreement with the accelerometer. On the other hand, for the stroke participant, DLC estimations for all kinematic features predominantly reflect data from the accelerometer. Across all datasets, AUC has the smallest PMSE values, suggesting that, based on our data, motor effort and energy expenditure in the tasks are best represented by DLC. Additionally, PMSE values for the stroke dataset are higher than those for the control, highlighting DLC's limitations in accurately detecting finer details of motion data in individuals with UE impairments. The results indicate that DLC reasonably estimates kinematic data for both participants, although further refinement of the methods is necessary to enhance the analysis of stroke data.

<p dir="ltr">During many biological processes, cells move through their surrounding environment by exerting mechanical forces. The mechanical forces are mainly generated by molecular interactions between actin filaments (F-actins) and myosin motors within the actin cytoskeleton. Forces are transmitted to the surrounding extracellular matrix via adhesions. In this thesis, we employed agent-based computational models to study the interactions between F-actins and myosin in the motility assay and the cell migration process. In the first project, the myosin motility assay was employed to study the collective behaviors of F-actins. Unlike most of the previous computational models, we explicitly represent myosin motors. By running simulations under various conditions, we showed how the length, bending stiffness, and concentration affect the collective behavior of F-actins. We found that four distinct structures formed: homogeneous networks, flocks, bands, and rings. In addition, we showed that mobile motors lead to the formation of distinct F-actin clusters that were not observed with immobile motors. In the second project, we developed a 3D migration model to define how cells mechanically interact with their 3D environment during migration. Unlike cells migrating on a surface, cells within 3D extracellular matrix (ECM) must remodel the ECM and/or squeeze their body through the ECM, which causes 3D cell migration to be significantly more challenging than 2D migration. Our model describes realistic structural and rheological properties of ECM, cell protrusion, and focal adhesions between cells and the ECM.</p>

Background and Aims Stent migration and subsequent adverse events are frequently observed in the use of fully covered self-expandable metal stents (FCSEMSs) for distal biliary stenosis. In this study, we identified predictors for stent migration based on biomechanical stent characteristics and associated these findings with clinical outcomes. Methods The migration resistance of FCSEMSs was quantified by measuring the pull-out force. We analyzed a single-center retrospective cohort of 178 FCSEMSs for treatment success and adverse events occurring during 180 days of follow-up. Results Biomechanical measurements revealed a 4-fold higher migration resistance of FCSEMSs with anchoring fins (AF-FCSEMSs; Fmax = 14.2 ± .1 N) compared with FCSEMSs with flared ends (FE-FCSEMSs; Fmax = 3.8 ± 1.0 N; P < .0001). Clinically, AF-FCSEMSs showed lower rates of migration compared with FE-FCSEMSs (5% vs 34%, P < .0001). Unscheduled ERCP procedures because of stent dysfunction were less frequent in the AF group compared with the FE group (15% vs 29%, P = .046). Cholangitis because of stent dysfunction was observed in 5% of the AF group compared with 19% in the FE group (P = .02). Stent patency rates at 1, 3, and 6 months were higher in the AF group (96%, 90%, and 80%, respectively) compared with the FE group (90%, 74%, and 66%; log-rank test: P = .03). Conclusions The pull-out force as a biomechanical stent property predicts the migration resistance of FCSEMSs in distal biliary stenosis and may thus be used to classify stents for this application. AF-FCSEMSs showed a significantly lower rate of migration and adverse events compared with FE-FCSEMSs.

Yes / In this paper we use multivariate statistical techniques to gain insights into how adaptive gait involving obstacle crossing is regulated in lower-limb amputees compared to able-bodied controls, with the aim of identifying underlying characteristics that differ between the two groups and consequently highlighting gait deficits in the amputees. Eight unilateral trans-tibial amputees and twelve able-bodied controls completed adaptive gait trials involving negotiating various height obstacles; with amputees leading with their prosthetic limb. Spatiotemporal variables that are regularly used to quantify how gait is adapted when crossing obstacles were determined and subsequently analysed using multivariate statistical techniques. There were fundamental differences in the adaptive gait between the two groups. Compared to controls, amputees had a reduced approach velocity, reduced foot placement distance before and after the obstacle and reduced foot clearance over it, and reduced lead-limb knee flexion during the step following crossing. Logistic regression analysis highlighted the variables that best distinguished between the gait of the two groups and multiple regression analysis (with approach velocity as a controlling factor) helped identify what gait adaptations were driving the differences seen in these variables. Getting closer to the obstacle before crossing it appeared to be a strategy to ensure the heel of the lead-limb foot passed over the obstacle prior to the foot being lowered to the ground. Despite adopting such a heel clearance strategy, the lead-foot was positioned closer to the obstacle following crossing, which was likely a result of a desire to attain a limb/foot angle and orientation at instant of landing that minimised loads on the residuum (as evidenced by the reduced lead-limb knee flexion during the step following crossing). These changes in foot placement meant the foot was in a different part of swing at point of crossing and this explains why foot clearance was considerably reduced in amputees. The results highlight that trans-tibial amputees use quite different gait adaptations to cross obstacles compared with controls (at least when leading with their prosthetic limb), indicating they are governed by different constraints; seemingly related to how they land on/load their prosthesis after crossing the obstacle. / Yes

Computational fluid dynamic models for porous lattice scaffolds are one of the few significant methods of determining the viability of a structure for in vivo applications. The most important property analyzed to determine this is fluid induced Wall Shear Stress (WSS) exhibited throughout the structure. This property has key ranges that are specifically identified and closely analyzed. Three different geometries, 2 TPMS structures and 1 non-TPMS structure are modeled and discussed. Three different models for each geometry are developed with porosities of 62, 70 and 80 percent. The Voronoi yields the best results, with WSS values well within the desired criteria for osteogenesis, minimizing cell death and detachment, and maximizing osteoblast and osteocyte generation. The outcome of this thesis helps reinforce the Voronoi lattice structure in bone tissue engineering applications. Further in vitro and in vivo experimentation is required to verify the results of this CFD analysis.