Institute for BiomechanicsOpen OpportunitiesFollowing trauma or due to degeneration it can be necessary to replace one or more intervertebral discs with an implant, a so-called Total Disc Replacement (TDR). Such devices enable motion though surfaces articulating against each other. While this treatment is clinically successful, it is connected to considerable complication and reoperation rates. Therefore, we are optimizing the design of such an implant to address these issues.
While many different designs and design types have been proposed and are used in clinical practice, there is no consensus on what design or design type is the most beneficial. However, it is hypothesized, that replicating the situation that is present in healthy (asymptomatic) subjects as closely as possible, is optimal. Since the motions of the cervical spine are coupled (coupling of rotation and translation as well as multiple rotations) the optimal design of the articulating surfaces is not obvious. Therefore, this master’s thesis project aims at designing the implants articulating surfaces using parametric design optimization in LS-OPT based on finite element simulations. - Engineering and Technology
- Master Thesis
| Background:
The Laboratory of Orthopedic Technology has recently developed a novel joint implant and is undergoing optimization of the manufacturing process. We are looking for a master's student who is passionate about medical devices and mechanical design to join us for a semester project.
Objectives:
• Design different molds for material casting using SolidWorks or Fusion 360.
• Optimize implant using matlab or Python.
• Utilize 3D printing or laser cutting to create the molds.
• Conduct mechanical tests on the implants.
Your Profile:
• Strong knowledge in mechanical design and drawing skills.
• Hands-on and detail-oriented.
• Experience with SolidWorks or Fusion 360, as well as Python or Matlab.
Timeframe:
Starting ASAP until the end of September.
- CAD/CAM Systems, Flexible Manufacturing Systems, Mechanical Engineering, Polymers
- ETH Zurich (ETHZ), Semester Project
| Parkinson’s disease is one of the most common neurodegenerative movement disorders affecting over 10 million people worldwide. Symptoms like impaired gait and postural instability can cause falls and highly impair patients’ mobility. The consequences of falls include fractures, hospital admissions, loss of independence, fear of falls, social isolation and early mortality. Falls are cited as one of the worst aspects of PD and unfortunately few efficacious interventions are available. - Engineering and Technology, Medical and Health Sciences
- Master Thesis, Semester Project
| Accurate non-invasive assessment modalities that incorporate both scapular motion and its morphology are currently unavailable, presenting a clear need for sustainable clinical application. To address this need, the Laboratory for Movement Biomechanics (LMB) utilizes a unique optical 4D scanning system (SLOT) to estimate the underlying anatomical structures using non-invasive structured light to produce high-quality images of the human skin surface, both statically and dynamically. By utilizing the clear cutaneous surface contours surrounding the scapula, the application of this technology to the shoulder joint could allow a novel non-invasive and dynamic approach for estimating scapular kinematics that overcomes the challenges associated with soft-tissue artifacts. The key challenge in the development of this approach is the precise identification and tracking of relevant scapula landmarks, as well as soft tissue artifacts, all of which are expected to affect the accuracy of the SLOT-measured kinematics. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
| Knee kinematics is critical for diagnosing pathologies such as osteoarthritis and providing guidance for implant design. Estimating knee kinematics requires aligning a model with a target X-ray image. This estimation process, often implemented by human labor, can be very time-consuming. This research aims to use a deep learning network to estimate the pose (kinematics) from X-ray images, partially replacing manual labor. Such a network should predict a pose from a current fluoroscopic image. By the end of this project, a robust pipeline should be completed, achieving baseline performance to provide convincing pose estimation for images from different modalities (single-plane system & dual-plane system; natural bone model & implant model). - Biomechanics, Biomedical Engineering, Computer Vision
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Combine two exploding fields in computer science: machine learning and agent-based modelling.
Based on preclinical and in vitro studies of cell behaviour and cytokine reaction-diffusion and mechanical tests we have generated an in-house biofidelic agent-based model of the human skeleton and its response to diseases and their treatments. This model reproduces the effects of several widely used osteoporosis treatments on key parameters used to quantify fracture risk. This rule-based approach involves studying bone mechanobiology at the cell scale and extrapolating this to millions of cells at the tissue scale to understand the pharmacokinetics of treatments and identify possible new therapies and approaches to patient-specific treatment.
An alternative approach to in silico prediction of response to treatment is a supervised learning approach where we simply input baseline and follow-up bone scans to a CNN with twelve layers constructed using keras. We then attempt to dive into the black box and quantify what characteristics of the input govern the response of our model. The issue is the clinical data is not big enough to do this well so we use the agent-based model as input to the ML approach to construct a proxy model! This also helps us understand, validate and quantify the uncertainty in the agent-based model. To decide which runs of the agent-based model to use as input to the ML approach to construct the proxy model we use polynomial chaos expansion. - Animal Physiology-Cell, Artificial Intelligence and Signal and Image Processing, Cell Development (incl. Cell Division and Apoptosis), Cellular Interactions (incl. Adhesion, Matrix, Cell Wall), Computation Theory and Mathematics, Modeling and Simulation, Protein Targeting and Signal Transduction
- Bachelor Thesis, Master Thesis, Semester Project
| Rare genetic disorders are defined by a prevalence of fewer than 1/2000 people, are chronic and affect patients throughout their lifespan. Osteogenesis imperfecta (OI) is a heterogeneous group of rare genetic bone disorders. OI is a debilitating condition that involves impaired mobility, high fracture incidence and subsequent limb deformities. No treatment exists today that targets the underlying abnormal collagen structure and organization. The mainstay in pediatric care of OI remains antiresorptive therapy with bisphosphonates, despite concerns of long-term effects on depressed bone turnover. While antiresorptive monoclonal antibody treatments are currently undergoing clinical trials in children and young adults, anabolic treatments that directly increase bone formation are currently approved for adults only and decrease in efficacy over a relatively short time span. The experience with these drugs in OI therapy is limited, as clinical studies are still ongoing.
- Biomedical Engineering, Mechanical and Industrial Engineering
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| This project endeavors to explore the dynamic interplay among calcium ions, bone graft substitutes, and resident immune cells in both orthotopic and ectopic environments, employing advanced ratiometric imaging techniques. - Biomaterials, Cellular Interactions (incl. Adhesion, Matrix, Cell Wall)
- Bachelor Thesis, Internship, Master Thesis, Semester Project
| Our goal is to establish a heterocellular 3D printed bone organoid model comprising all major bone cell types (osteoblasts, osteocytes, osteoclasts) to recapitulate bone remodeling units in an in vitro system. The organoids will be produced with the human cells, as they could represent human pathophysiology better than animal models, and eventually could replace them. These in vitro models could be used in the advancement of next-generation personalised treatment strategies. Our tools are different kinds of 3D bioprinting platforms, bio-ink formulations, hydrogels, mol-bioassays, and time-lapsed image processing of micro-CT scans. - Biomaterials, Biomechanical Engineering, Cell Development (incl. Cell Division and Apoptosis), Cellular Interactions (incl. Adhesion, Matrix, Cell Wall), Polymers
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Parkinson's disease is a prevalent neurodegenerative condition in individuals over 60 years old. It results from impaired dopaminergic cells in the basal ganglia, leading to gait disturbances and reduced independence. While treatment options like dopamine replacement therapies and Deep-Brain Stimulation (DBS) exist, not all patients benefit from DBS. The lack of reliable biomarkers hampers understanding of surgical outcomes. A new DBS device enables wireless recording of subcortical brain activity, offering novel insights into Parkinson's subcortical activity. To explore personalized therapies, this study will measure the gait performance, neuro-activities like deep brain activity as well as electroencephalography (EEG) during walking in Parkinson's patients. Combining cortical (EEG) and subcortical (DBS) recordings aim to investigate comprehensive brain activity during pathological gait. - Information, Computing and Communication Sciences, Medical and Health Sciences
- Collaboration, Internship, Lab Practice, Master Thesis, Semester Project
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