ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC)Acronym | RESC | Homepage | https://resc.ethz.ch/ | Country | Switzerland | ZIP, City | | Address | | Phone | | Type | Academy | Parent organization | ETH Zurich | Current organization | ETH Competence Center - Competence Center for Rehabilitation Engineering and Science (RESC) | Child organizations | | Members | |
Open OpportunitiesThe goal of the project is to develop a wearable device capable of non-invasive measurement of human biomarkers related to performance and fatigue during exercise. - Chemistry, Engineering and Technology, Medical and Health Sciences
- Master Thesis
| The goal of the project is to synthesize and characterize a number of small molecules capable of acting as mechanophore addition to various polymers. These polymers would then be used as wearable strain or pressure sensors. - Chemical Engineering, Chemistry, Composite Materials
- Master Thesis
| 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
| The goal of the project is to modify commercially available conductive yarns to improve their operational properties for potential employment in novel garment-embedded sensors for human motion detection. - Engineering and Technology, Medical and Health Sciences, Other Chemistry
- Semester Project
| Digital humans are a very popular and fast-growing area with manifold applications in AR/VR. However, the dynamic of the existing head avatars is mostly limited to the facial region. In this project, we will focus on realistically rendered avatars that would include realistic modeling of both faces and hair with physically accurate dynamics and interactions. - Information, Computing and Communication Sciences
- ETH Zurich (ETHZ), Master Thesis, Semester Project
| 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 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 process of evaluating sleep examinations and diagnosing sleep disorders through polysomnographies (PSGs) is labor-intensive as it requires manual analysis from sleep technicians and doctors. In collaboration with Clinic Barmelweid, a leading sleep and rehabilitation clinic in northwestern Switzerland, we plan to automate this process using machine learning models. Clinic Barmelweid conducts approximately 400-450 PSGs annually and has access to a dataset of more than 5,000 recordings. - Artificial Intelligence and Signal and Image Processing, Biomedical Engineering, Medical and Health Sciences
- Collaboration, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Pulmonary hypertension (PH) in newborns poses significant diagnostic challenges due to its association with various diseases and its impact on morbidity and mortality. Early and accurate detection is essential for effective management, yet current manual echocardiographic assessment is time-consuming and requires expertise. This project aims to develop an automated machine learning method using multimodal variational autoencoders (VAEs) and diffusion models to predict PH in newborns from ultrasound, ECG data, and clinical variables. Leveraging a cohort of 270 newborns from the University Children’s Hospital Regensburg, the project will enhance interpretability and feature representation by assessing the significance of each data type and utilizing synthetic data augmentation. The hybrid approach of combining VAEs with diffusion models is expected to improve prediction accuracy and generalization, advancing early detection and understanding of PH in newborns. - Biomedical Engineering, Computer Communications Networks, Electrical and Electronic Engineering, Image Processing, Signal Processing
- ETH Zurich (ETHZ), Master Thesis
| The goal of the project is to develop and test a smart sock prototype for plantar pressure measurements. The smart sock contains textile based pressure sensors and a readout module. This technology can be used for plantar pressure monitoring in diverse wearable applications ranging from healthcare to sports. - Biomedical Engineering, Medical and Health Sciences
- Master Thesis
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