Student Projects

Project Descriptions

Additional projects are always available. Please consult our list of ongoing research projects  and contact the involved people listed on the top right to enquire about additional projects.


Special projects/internships:

ETH Zurich uses SiROP to publish and search scientific projects. For more information visit sirop.org.

Exploring upper limb impairments using explainable AI on Virtual Peg Insertion Test data

This thesis aims to apply explainable AI techniques to analyze time series data from the Virtual Peg Insertion Test (VPIT), uncovering additional metrics that describe upper limb impairments in neurological subjects, such as those with stroke, Parkinson's disease, and multiple sclerosis. By preserving the full dimensionality of the data, the project will identify new patterns and insights to aid in understanding motor dysfunctions and support rehabilitation.

Keywords

Machine learning, rehabilitation, neurology, upper limb, impairment, explainable AI, SHAP, novel technology, assessment, computer vision, artificial intelligence

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Master Thesis

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Published since: 2025-12-05 , Earliest start: 2026-01-05

Organization Rehabilitation Engineering Lab

Hosts Domnik Nadine

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Mapping Statistical and Methodological Practices in Non-Invasive Brain Stimulation for Stroke Rehabilitation Research: Contribution to a Scoping Review

Understanding and predicting how and why individuals respond to non-invasive brain stimulation (NIBS) is one of the major challenges in current neurorehabilitation research. Although a growing number of studies propose predictors of treatment response, the statistical approaches used in this field vary widely. This makes it difficult to compare results, assess reliability, or build robust personalized rehabilitation tools. An ongoing project at the RELab aims to systematically map how statistical and methodological practices are used to define, assess, and predict NIBS response across the rehabilitation literature. This forms the foundation of a larger research project on biomarker-guided neurorehabilitation. This student project involves conducting a scoping review of several studies, examining how researchers define “responders,” what statistical models they use, and how prediction frameworks are validated. This internship is ideal for a motivated student interested in neurorehabilitation, data science, and research methodology.

Keywords

non-invasive brain stimulation, statistical methods, predictors, scoping review, personalized medicine, neurorehabilitation, research methodology, bibliographic research

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Semester Project , Internship

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Published since: 2025-12-03 , Earliest start: 2026-01-01 , Latest end: 2026-08-01

Organization Rehabilitation Engineering Lab

Hosts Perrin Cléo

Topics Medical and Health Sciences

Evaluating Engagement and Adherence to Robot-Assisted Rehabilitation: Can Large Language Model-Based Conversational Agents Support Stroke and TBI Patients During Unsupervised Therapy?

Stroke and traumatic brain injury (TBI) are major causes of long-term disability, often requiring intensive rehabilitation to restore motor function, particularly in the hands. While robotic-assisted therapy and mobile health (mHealth) applications offer promising tools for recovery, sustaining patient engagement outside clinical environments remains a significant challenge. This project explores the use of the RehabCoach app and ReHandyBot device in a hybrid rehabilitation program (i.e., two weeks in-clinic followed by six weeks of unsupervised home therapy). The focus is on collecting and analyzing conversational data between patients and the app’s large language model (LLM)-based conversational agent to evaluate how these interactions influence therapy adherence and engagement.

Keywords

Stroke rehabilitation, traumatic brain injury, mobile health, conversational AI, large language models, therapy adherence, unsupervised rehabilitation

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Semester Project , Master Thesis

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Published since: 2025-11-11 , Earliest start: 2025-11-16 , Latest end: 2026-09-30

Organization Rehabilitation Engineering Lab

Hosts Retevoi Alexandra

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology , Behavioural and Cognitive Sciences

Efficient data processing and reporting in stroke neuro-rehabilitation

Project goal is to optimise existing and develop new algorithms into an efficient system for signal pre-processing, data storage, analysis and visualization in motor-neurorehabilitation. This data is generated by stroke patients wearing motion sensors during their therapy sessions. Key endpoint of the project is to display real-time and longitudinal therapy results, which can aid therapists and patients. The results of the project will help develop a more efficient therapy and is a key part of a larger project that seeks to develop an intelligent and closed-loop neural stimulation system for stroke rehabilitation.

Keywords

health biomarkers, data science, computer science, data visualization, data processing, real-time, internet of medical things, IoMT, healthcare internet of things, healthcare IoT

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Semester Project , Internship , Master Thesis

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Published since: 2025-10-08 , Earliest start: 2023-05-09

Organization Rehabilitation Engineering Lab

Hosts Donegan Dane , Viskaitis Paulius

Topics Medical and Health Sciences , Information, Computing and Communication Sciences , Engineering and Technology

Real-time control of neural stimulation for stroke patients.

Real-time analysis of movement kinematics can benefit multiple different strategies in rehabilitation after stroke, including allowing closed-loop brain stimulation. Use of inertial measurement units (IMUs) allows detection of movement and extraction of kinematic features, but application in real-time remains challenging. This project will develop algorithms for real-time movement data analysis and feature extraction in typical rehabilitation tasks and general real-life movements. In turn, these algorithms will be applied to control novel brain stimulation approaches in stroke neurorehabilitation.

Keywords

Inertial measurement unit, IMU, movement tracking, machine learning, real-time, signal processing

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Semester Project , Master Thesis

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Published since: 2025-09-02 , Earliest start: 2023-05-09

Organization Rehabilitation Engineering Lab

Hosts Viskaitis Paulius , Donegan Dane

Topics Engineering and Technology

Mechanistic Evaluation of taVNS in Motor Adaptation for Stroke Rehabilitation

This study aims to evaluate the mechanisms by which transauricular vagus nerve stimulation (taVNS) may facilitate motor learning and adaptation, focusing on reticulospinal tract (RST) activation. A set of assessments will be used to build a comprehensive neurophysiological profile, providing insights relevant to developing taVNS-based clinical interventions. In this role, you will engage in study design, data collection, and analysis, gaining hands-on experience in mechanistic neurophysiological research with direct clinical applications.

Keywords

Transauricular vagus nerve stimulation (taVNS) Reticulospinal tract (RST) Motor learning StartReact paradigm Stroke rehabilitation Neurophysiology Multisite EMG Motor pathway activation Clinical neurostimulation

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Semester Project , Internship , Bachelor Thesis , Master Thesis

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Published since: 2025-08-04 , Earliest start: 2024-11-24 , Latest end: 2025-10-26

Organization Rehabilitation Engineering Lab

Hosts Viskaitis Paulius

Topics Medical and Health Sciences , Engineering and Technology

Studies on Mechatronics

If you would like to carry out a Studies on Mechatronics project in our group, please contact the assistant working on, or closest to, the research topic you are interested in.

We currently have an open studies on mechatronics project aiming to evaluate and compare mechatronic designs for sensory/mechanical stimulation and massage of the feet. If interested, please contact .

Your Own Project Ideas?

It is always possible to find a project for motivated students with innovative ideas in the fields of rehabilitation, assistive and healthcare technology as well as haptics and motor learning. Please contact us if you would like to pursue a project which is not on the list above.

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