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 Opportunities12-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
| This project aims to revolutionize the analysis of electroencephalography (EEG) data by developing a specialized foundational model utilizing the principles of artificial intelligence. Despite the critical role of EEG in diagnosing and treating neurological disorders, challenges such as low signal-to-noise ratios and complex signal patterns hinder practical analysis. By adapting strategies from successful domains like natural language processing and computer vision, this project will build a machine learning model tailored for EEG signals. The model will undergo extensive pre-training on diverse EEG datasets to establish a robust understanding of neural activities, followed by fine-tuning for specific clinical tasks such as seizure detection and sleep stage classification. Our approach promises to enhance the accuracy, efficiency, and accessibility of EEG diagnostics, paving the way for improved patient outcomes. Validation and testing using standard performance metrics will measure the model's efficacy, setting a new standard in EEG analysis. - Electrical Engineering, Neural Networks, Genetic Alogrithms and Fuzzy Logic, Pattern Recognition, Signal Processing, Simulation and Modelling
- ETH Zurich (ETHZ), 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
| The widespread adoption of wearable technology enables continuous monitoring of physiological parameters like activity levels, heart rate, and sleep patterns. This study investigates the relationship between wearable measures and well-being, focusing on physical and mental health as well as overall quality of life. - Artificial Intelligence and Signal and Image Processing
- ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| This study aims to detect voice pathologies distinguishing homophonic from dysphonic labels. - Information, Computing and Communication Sciences
- Internship, Master Thesis, Semester Project
| This study aims to investigate the relationship between cough and health status among heart failure patients, recognizing cough as a potential indicator of underlying health status and symptom severity. - Information, Computing and Communication Sciences
- Internship, Master Thesis, Semester Project
| The project investigates the development of a co-axial extrusion methods for large-scale 3D printing bio-cementation structures. The extruded paste will host microorganisms such as S.Pasteurii, capable of precipitating calcite (MICP) to create bio-concrete structures. A robotic paste 3D printing platform will be used for the fabrication process; the bio-paste will be precipitated and calcified by the bacterial activity reinforcing the material. - Architecture, Urban Environment and Building, Chemistry, Engineering and Technology
- Bachelor Thesis, Master Thesis, Semester Project
| 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
| The efficient operation of excavators in construction environments necessitates precise pose estimation of their buckets. Current methods rely on IMUs placed on the excavator arm which require tedious calibration and can be damaged during construction operations. This project aims to leverage computer vision and machine learning to enhance pose estimation, thereby enabling VR overlays for teleoperation and facilitating automation tasks. - Information, Computing and Communication Sciences
- 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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