 Rehabilitation Engineering LabOpen OpportunitiesThis project aims to develop a clinically usable electrode for transcutaneous vagus nerve stimulation (tVNS) therapy. The objective is to create an electrode that is biocompatible, low-impedance, and easy to use, allowing patients to apply it themselves with minimal setup time. The project involves conducting a literature review, evaluating existing designs, selecting appropriate materials, developing a prototype, and assessing its efficacy and usability in a clinical setting. The outcome will be an electrode that enhances the convenience and effectiveness of tVNS therapy, contributing to improved patient treatment adherence and outcomes. - Biomedical Engineering, Materials Engineering, Mechanical and Industrial Engineering
- Internship, Master Thesis, Semester Project
| This project explores how gamification elements in smartphone applications can keep patients engaged during unsupervised at-home physical therapy. Integrated with the upper-limb rehabilitation robotic device ReHandyBot, the RehabCoach app currently tracks basic metrics like time spent with the device and exercise levels. However, to improve adherence and motivation, this project aims to redesign the feedback system, incorporating features such as badges and personalized progress visualizations. By enhancing these features, the goal is to support patients in staying engaged and committed to their therapy regimens, ultimately improving long-term outcomes. - Behavioural and Cognitive Sciences, Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
- Bachelor Thesis, ETH Zurich (ETHZ), Internship, Master Thesis, Semester Project
| Join our research project focused on analysing complex neurophysiological data collected during non-invasive brain stimulation experiments. This project aims to optimise brain stimulation protocols for future stroke rehabilitation by investigating neural responses to various stimulation parameters. The data includes electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmography (PPG), inertial measurement unit (IMU) readings, pupilometry, and galvanic skin response (GSR). We aim to model brain states based on these measurements to define brain circuitry outcomes from stimulation and movement interactions, using advanced techniques like connectivity-based biomarkers. This modeling will help generalise findings to broader brain states, such as valence, attention, and stress. - Applied Statistics, Biological Mathematics, Neurosciences, Simulation and Modelling
- Master Thesis
| Neurological patients frequently experience upper limb sensorimotor impairment, necessitating effective rehabilitation strategies to restore functionality. Accurate assessments of patient movements are integral to these strategies, requiring precise measurement tools. The rapid advancements in AI pose estimation and biomechanical modeling offer a promising solution: a low-budget, user-friendly tool for accurately measuring patient movements in diverse settings. We are developing such a tool, iMove, which leverages video-based AI technology to provide clinical-grade precision.Your role will involve improving iMove's graphical user interface (GUI) and algorithms, as well as testing its performance and usability in collaboration with researchers, clinicians, and potentially patients. - Engineering and Technology, Information, Computing and Communication Sciences, Medical and Health Sciences
- Bachelor Thesis, Collaboration, Course Project, Internship, Lab Practice, Master Thesis, Semester Project
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