 Spinal Cord Injury & Artificial Intelligence LabOpen OpportunitiesThis 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 study examines transfer learning to enhance activity recognition in SCI patients using wearable sensors and existing datasets. - Artificial Intelligence and Signal and Image Processing, Biomechanical Engineering, Electrical Engineering, Human Movement and Sports Science, Mechanical Engineering, Rehabilitation Engineering
- Internship, Master Thesis
| This thesis explores precise event segmentation in time-series/video data from wearable sensors to monitor daily activities in spinal cord injury individuals. - Biomedical Engineering, Computer Vision, Electrical Engineering, Engineering/Technology Instrumentation, Mechanical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition, Signal Processing
- Internship, Master Thesis, Semester Project
| Osteoarthritis (OA) presents a significant challenge in healthcare, necessitating innovative solutions to alleviate pain, enhance mobility. This thesis documents the research and development journey of an OA knee orthosis within the Spinal Cord and Artificial Intelligence Lab (SCAI-Lab) at ETH Zurich.
This thesis is a close collaboration between the ORTHO-TEAM Group and the SCAI-Lab at ETH Zurich. The collaboration offers a unique exchange of expertise and resources between industry and academia. Together, we aim to make meaningful progress in the field of and empower students to make valuable contributions to their academic pursuits.
- Biomechanics, Biomedical Engineering
- ETH Zurich (ETHZ), Master Thesis
| This project aims to develop a novel approach for tracking a person's health condition changes using daily life data, biosignals, and nearable information. The Life-long-logging system provides meaningful data for medical staff and directly engages patients and their caregivers. We integrate people's health status within a sensory system encompassing wearables and nearables embedded within the person's life without being obtrusive. This enables continuous tracking of users' health states. To obtain reliable data, we integrate tested medical class biosensors and validate the data with specific patient populations, caregivers, doctors, and robot experts. Additionally, we develop a graphical model to visualize the relationship between clinical information, remote sensing information, environmental factors, and robot-acquired data. This model will predict health status change from robot interventions and generate a meaningful inference about a person's state. A digital representation - above all, the digital twin - bridges the gap between the physical and virtual system, improving the interpretation of reality using sound data collection and interpretation. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| This project aims to develop a novel approach for tracking a person's health condition changes using daily life data, bio signals, and nearable information. The Life-long-logging system provides meaningful data for medical staff and directly engages patients and their caregivers. We integrate people's health status within a sensory system encompassing wearables and nearables embedded within the person's life without being obtrusive. This enables continuous tracking of users' health states. To obtain reliable data, we integrate tested medical class biosensors and validate the data with specific patient populations, caregivers, doctors, and robot experts. Additionally, we develop a graphical model to visualize the relationship between clinical information, remote sensing information, environmental factors, and robot-acquired data. This model will predict health status change from robot interventions and generate a meaningful inference about a person's state. A digital representation - above all, the digital twin - bridges the gap between the physical and virtual system, improving the interpretation of reality using sound data collection and interpretation. - Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| The project aims to advance autonomous navigation in highly dynamic environments by developing a comprehensive pipeline that processes pointcloud-based data, people detections, and tracks to generate a dynamic map of public spaces. This involves enhancing ground truth generation, selecting and training state-of-the-art deep learning models for space segmentation, and improving simulation scenarios in NVIDIA Isaac Sim. The end goal is to improve navigation strategies and the understanding of assistive robots in public spaces, bridging the gap between current technologies and future advancements in autonomous navigation. - Computer Vision, Image Processing, Intelligent Robotics, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition, Simulation and Modelling
- 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
| Join a team of scientists improving the long-term prognosis and treatment of Spinal Cord Injury (SCI) through mobile and wearable systems and personalized health monitoring.
Joining the SCAI Lab part of the Sensory-Motor Systems Lab at ETH, you will have the unique opportunity of working at one of the largest and most prestigious health providers in Switzerland: Swiss Paraplegic Center (SPZ) in Nottwil (LU). - Artificial Intelligence and Signal and Image Processing, Computer Software, Data Format, Information Systems
- ETH Zurich (ETHZ), Internship, Lab Practice, Student Assistant / HiWi
| 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
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