Sensory-Motor Systems LabOpen OpportunitiesCartilage damage in the knee joint can be caused by aging or repetitive actions. It can be treated by surgically removing the damaged cartilage tissue and filling the generated defect with a precisely shaped, healthy cartilage graft. Removing the defected cartilage is commonly done with surgical curettes. We are investigating the use of laser ablation for a more precise defect preparation process. With two different lasers, we managed to obain promising results regarding cell viability in live samples. However, laser parameters such as pulse frequency and energy need to be optimized towards higher cutting efficiency. Your task will be to prepare a setup to test, optimize, and validate various parameter sets using different lasers for articular cartilage ablation. - Biomedical Engineering, Optical Physics
- Master Thesis
| Despite the growing amount of work on applying causal discovery method with expert knowledge to areas of interest, few of them inspect the uncertainty of expert knowledge (what if the expert goes wrong?). This is highly important since that in scientific fields, causal discovery with expert knowledge should be cautious and an approach taking expert uncertainty into account will be more robust to potential bias induced by individuals. Therefore, we aim to develop an iterative causal discovery method with experts in the loop to enable continual interaction and calibration between experts and data.
Based on the qualifications of the candidates, we can arrange a subsidy/allowance for covering traveling or living costs. - Expert Systems, Health Information Systems (incl. Surveillance), Statistics
- Internship, Master Thesis, Semester Project
| This project will be based on the preliminary results obtained from a previous master project in causal graphical modeling of autonomous dysreflexia (AD). The focus of the extension would be two-fold. One is improving the temporal graphical reconstruction for understanding the mechanism of AD. The other one is building a forecasting framework for the early detection and prevention of AD using the graph structure we constructed before. Please refer to the attached document for more details about the task description. Based on the candidate's qualifications, funding/allowance can be provided. - Artificial Intelligence and Signal and Image Processing, Autonomic Nervous System
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| This project focuses on developing an explainable Artificial Intelligence (xAI) framework based on graphical modeling (GM), to enhance the capacity and capability of medical AI. Collaborating with the Swiss Paraplegic Centre (SPZ) for validation, our goal is to improve the long-term prognosis of spinal cord injury (SCI) individuals. Through medical records and a multimodal sensory monitoring system, we aim to create digital twins capable of integrating diverse data sources, guiding medical treatment, and addressing common secondary health conditions in the SCI population. The envisioned GM-based digital twin (GMDT) will represent hierarchical relations across demographic features, functional abilities, daily activities, and health conditions for SCI individuals, allowing for downstream tasks such as prediction, causal inference, and counterfactual reasoning. The assimilation and evolution between the physical and digital twins will be implemented under the GM framework, promising advancements in personalized healthcare strategies and improved outcomes for SCI people. Please refer to the attached document for more details about the task description. Based on the candidate's qualifications, funding/allowance can be provided. - Biomedical Engineering, Digital Systems, Knowledge Representation and Machine Learning, Pattern Recognition, Simulation and Modelling
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The primary objective of this project is to develop an automated pipeline for the identification and recognition of patterns within urodynamic recordings, utilizing urodynamic recording data in conjunction with annotated patterns provided by experts. This endeavor seeks to reduce the susceptibility of interpreting urodynamic recordings to potential errors arising from human judgment and inaccuracies, thereby improving the management of urinary tract complications in patients with spinal cord injury. By implementing a systematic approach to pattern recognition in Bladder Valomue/Pressure Time Series Measurements of urodynamic data, the potential for error in decision-making can be significantly reduced. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Biosensor Technologies, Computer Hardware, Computer-Human Interaction, Electrical and Electronic Engineering, Engineering/Technology Instrumentation, Mechanical Engineering, Medical Biotechnology
- Internship, Master Thesis, Semester Project
| Gait patterns in multiple impairments present unique and complex patterns, which hinders the proper quantitative assessment of the walking ability for chronic ambulatory conditions when translated to daily living. In this project, we will focus on finding clusters of gait patterns through unsupervised learning from a large dataset of incomplete spinal cord injury individuals. The goal is to investigate hidden patterns in relation to the type of injuries and find their application for future diagnosis and rehabilitation treatment.
Your work will guide future rehabilitation methods in general clinical practice, through applied classification and dimensionality reduction in Biomechanics of walking.
Goal: Develop an unsupervised clustering pipeline for a large dataset of gait patterns from spinal cord injured individuals for class similarity evaluation
- Engineering and Technology, Expert Systems, Medical and Health Sciences, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition, Signal Processing, Simulation and Modelling
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis
| This hands-on work (internship or semester project) within a clinical setting will bring you close to intelligent health management while exploring multiple data systems. You will experience multimodal data of robotics rehabilitation, general clinical practice, and detailed clinical studies applied in classification and dimensionality reduction. - Biomechanics, Computer Graphics, Computer Vision, Computer-Human Interaction, Engineering and Technology, Expert Systems, Information Systems Development Methodologies, Information Systems Management, Intelligent Robotics, Interfaces and Presentation, Medicine-general, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Operating Systems, Pattern Recognition, Programming Techniques, Rehabilitation and Therapy: Occupational and Physical, Sensory Systems, Signal Processing, Simulation and Modelling, Software Engineering, Sports Medicine, Virtual Reality and Related Simulation
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Lab Practice, Master Thesis, Other specific labels, Semester Project
| Obstructive sleep apnea (OSA) affects 1 billion individuals globally. By developing an advanced sensor unit for unobtrusive, home-based monitoring, we want to collect sleep-related data and identify unique OSA features associated with treatment outcomes. The ultimate goal is to enhance personalized care, improve diagnosis, and optimize the efficacy of obstructive sleep apnea treatments. - Clinical Engineering
- Bachelor Thesis, Internship, Lab Practice, Master Thesis, Semester Project
| Modern robots collect data from various sensors. When these sensors operate independently, time-synchronization through rectification of their individual clocks and correction for temporal drift is required.
In our previous work, we developed an initial version of a synchronization pipeline in Python, designed for offline data synchronization. Our current pipeline already effectively synchronizes sensors that include a common external synchronization signal. Despite already working well, our current pipeline still requires some expertise to configure the data sources. To make the pipeline widely usable, we now need to make it function seamlessly even without expert knowledge and access to external synchronization signals. This enhancement should also extend to scenarios involving continuous online data as well.
Furthermore, we want to prove the correctness of the synchronization and showcase the performance based on synthetic data.
In essence, your thesis will comprise the following key objectives:
1. Understand the challenges involved in data synchronization.
2. Familiarize yourself with the existing synchronization pipeline.
3. Innovate strategies for achieving data synchronization without relying on external synchronization signals.
4. Enhance the user interface by creating an intuitive guide for using the pipeline effectively.
5. Extend the functionality to accommodate online data streams.
6. Assess the pipeline's correctness and performance using synthetic biosignals, as well as pre-recorded biosignals from the SMS-Lab and Tohoku University.
Throughout this project, you will receive guidance from me, a 4th year PhD candidate at the Sensory-Motor Systems Lab at ETH Zurich, and researchers at Tohoku University in Sendai, Japan. As I will be in Japan from October, we will conduct the weekly meetings over Zoom.
Furthermore, in case of interest, you have the exciting opportunity to visit us in Japan. This opportunity can be pursued either through personal funding or by applying for respective scholarships, such as the Heyning-Roelli Foundation, SEMP, Spickenreuther Foundation, and others. I have received scholarships in the past and I am happy to provide guidance and support throughout the application process. - Biosensor Technologies, Data Storage Representations, Data Structures, Digital Systems, Information Storage, Retrieval and Management, Pattern Recognition, Signal Processing, Simulation and Modelling, Software Engineering
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| The goal of this project is to develop a miniature milling feed mechanism that allows the milling instrument to move in the vertical direction for a miniature intraoral robot. - Engineering and Technology
- Master Thesis
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