Sensory-Motor Systems LabOpen OpportunitiesLucid dreaming allows individuals to be aware of and control their dreams, offering benefits for therapy, creativity, and skill enhancement. Techniques such as pre-sleep meditation improve lucid dream frequency and clarity. Sensory stimuli, synchronized with sleep stages, can further induce lucidity. This project aims to develop a closed-loop system to enhance lucid dreaming training and experience. The system will use recorded EEG data to detect sleep stages and combine pre-sleep meditation with sensory stimuli applied during the respective sleep stages. The lab's existing rocking bed “Somnomat” will be integrated to apply vestibular stimuli and additional sensory stimuli based on auditory or visual cues, triggered by physiological changes, or depending on a specific sleep stage. - Engineering and Technology
- ETH Zurich (ETHZ), 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
| 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
| We currently want to (i) elaborate the added value of a campus board that records the forces per limb, (ii) determine grasping phases for kinematic analyses of the phalanges more pragmatically than with 6DoF sensors, and (iii) drive forward a competition analysis based purely on video material. - Biomedical Engineering, Human Movement and Sports Science
- Internship, Semester Project
| Ski touring provides a unique and immersive outdoor experience, but the ascent can impose a considerable amount of strain on the body, especially for novices, elderly, or people with disabilities. The objective of this master thesis is to redesign an existing concept and functional model of an electric ski touring device that supports hill ascents, aiming to enhance the ski touring experience for individuals with lower fitness levels by making it less physically demanding and more enjoyable. The current model must be optimized with respect to weight, function, energy consumption, and usability (donning/doffing). After successful fabrication and testing, first steps shall be performed to identify intellectual property and market needs, and finally plan the commercialization of the e-touring ski. - Engineering and Technology
- Master Thesis
| 12-lead electrocardiograms (ECGs) are still solely documented on paper in many hospitals, especially in the Global South. These physical paper records provide a multitude of conditions recorded in many different countries. Our lab has access to a dataset with more than 8000 patient’s ECG photos / scans of 12-lead signals printed onto physical paper sheets. The dataset comprises 12-lead ECG image records from more than 35 hospital sites across Europe. The primary objective of this project is to develop an automated digitization pipeline from raw image scan in .png format towards 12 vectorized ECG time series in WFDB format. - Computer Vision, Engineering and Technology, Medical and Health Sciences
- Bachelor Thesis, 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
| We are developing a teleoperated micro-assembly system. A core component is a force-sensitive micro-gripper. A first gripper prototype has been realized and evaluated. Your task will be to review and improve the current design and to implement automated object slippage detection. - Mechanical and Industrial Engineering, Robotics and Mechatronics
- Master Thesis
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