Please check our positions below. If you are interested in joining our lab, contact nsquared@fau.de with a short description of your scientific background and what you would like to do, e.g. bachelor/master thesis.
Integration of online model recalibration into cursor control application
We are offering a thesis project focused on the integration of retraining across sessions as well as online model recalibration during real-time cursor control based on sEMG data recorded from legs and forearm.
Tasks:
- Review relevant literature
- Explore performance degradation and ways for model recalibration
- Integrate validated findings into existing applications
- Conduct experiments and evaluate performance
Requirements:
- Interest in biosignal processing and neural interfacing
- Very good programming experience in Python (experience with PySide6, SciPy, PyTorch/Scikit-learn is a plus)
- Solid knowledge of classical machine learning and deep learning
- Ability to work independently and systematically
Supervisor:
Amin Olamazadeh, M.Sc.; Annika Ritter, M.Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.
Validation Study of a custom-build 3D Hand Dynamometer
Planning, designing and conducting a validation study of a custom-built 3d hand dynamometer. The device is designed to measure isometric finger forces in various directions. The validation study will assess the reliability of the dynamometer across multiple recording sessions for all five digits during both single and multi-digit contractions.
Tasks:
- Develop a comprehensive plan for the validation study
- Design and implement experimental protocols to evaluate the dynamometer’s performance
- Collect and analyse data to assess the reliability and accuracy of the dynamometer
- Document the study design, methods, results, and conclusions
Requirements:
- Solid python skills
- Solid knowledge in CAD is beneficial
- Experience with git is beneficial
- Ability to work independently and sound time management skills
Supervisor:
Charlotte Pradel, M.Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.
Improved Design of a Hand Neuroorthosis for Children with Hemiparesis
This master’s thesis is jointly supervised by the Chair of Manufacturing Automation and Production Systems (FAPS) and the n-squared lab.
Motivation:
Hand function in childhood forms the foundation for lifelong independence and participation. Children with early unilateral brain lesions often develop severe paralysis of the contralateral hand. Despite the lack of visible movement, recent studies show that neural activity persists during attempted movements1 — too weak, however, to generate functional motion.
Using high-density surface electromyography (HD-sEMG) and advanced motor command decoding, these residual signals can be captured and translated into control commands. The goal of this project is to detect such volitional activity in real time and use it to control an active pediatric soft hand orthosis. Existing prototypes already demonstrate basic control, but further development is needed to make them suitable for daily-life use.
In these Master’s projects, you will work at the intersection of neurotechnology, rehabilitation, and robotics. Your contribution will help bring a pediatric neuroorthosis closer to clinical and functional maturity.
Tasks:
- Literature review (publications and patents)
- Designing a soft hand exoskeleton with improved range of motion
- Validation in children
- Possibility to co-design with therapists and young participants
Requirements:
- Bachelor in Mechatronics, Industrial Engineering, Medical Engineering or similar
- Good CAD skills
- Basic knowledge of robotics
- Strong interest in neurorehabilitation and human–machine interaction
- Ability to work independently in an interdisciplinary research team
Supervisor:
Pauline Wittermann, M. Sc.
Nico Weber, M. Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.
References:
Comparison of Intramuscular and High-Density Surface EMG for Detecting Regional Activation Differences in Vastus Medialis and Vastus Lateralis
Position description:
This thesis project investigates whether high-density surface electromyography (HD-sEMG) can detect regional activation differences within the quadriceps muscles, specifically between proximal and distal regions of the vastus medialis and vastus lateralis.
Previous work using intramuscular EMG (iEMG) demonstrated that selective or “split” activation between these regions is possible in most subjects. However, other studies using conventional surface EMG (sEMG) were not able to detect such regional differences.
The aim of this project is to directly compare iEMG and HD-sEMG recordings obtained from the same anatomical locations during voluntary selective activation tasks. HD-sEMG grids will be placed over proximal and distal regions of both muscles, while intramuscular electrodes will be inserted at corresponding sites. Participants will perform controlled contraction tasks and attempt region-specific activation. The recorded signals will be analyzed to determine whether HD-sEMG can reliably detect regional activation patterns comparable to those identified with iEMG. The study will contribute to understanding the spatial resolution limits of non-invasive EMG methods and their suitability for investigating fine neuromuscular control.
Tasks:
- Review relevant literature on regional muscle activation and EMG methodology
- Design and conduct EMG experiments
- Record and preprocess iEMG and HD-sEMG signals
- Compare regional activation patterns between methods
- Perform statistical analysis and interpret results
- Document findings in a scientific thesis
Requirements:
- Interest in neuromuscular physiology and biosignal processing
- Basic knowledge of EMG signal analysis
- Programming experience in Python or MATLAB is advantageous
- Ability to work independently and systematically
Supervisor:
Daniel Fenzel, M.Sc
Application:
Please provide a short CV and transcript of records to daniel.fenzel@fau.de.
References:
Validation Study of a custom-build 3D Hand Dynamometer
Planning, designing and conducting a validation study of a custom-built 3d hand dynamometer. The device is designed to measure isometric finger forces in various directions. The validation study will assess the reliability of the dynamometer across multiple recording sessions for all five digits during both single and multi-digit contractions.
Tasks:
- Develop a comprehensive plan for the validation study
- Design and implement experimental protocols to evaluate the dynamometer’s performance
- Collect and analyse data to assess the reliability and accuracy of the dynamometer
- Document the study design, methods, results, and conclusions
Requirements:
- Solid python skills
- Solid knowledge in CAD is beneficial
- Experience with git is beneficial
- Ability to work independently and sound time management skills
Supervisor:
Charlotte Pradel, M.Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.
Validation Study of a custom-build 3D Hand Dynamometer
Planning, designing and conducting a validation study of a custom-built 3d hand dynamometer. The device is designed to measure isometric finger forces in various directions. The validation study will assess the reliability of the dynamometer across multiple recording sessions for all five digits during both single and multi-digit contractions.
Tasks:
- Develop a comprehensive plan for the validation study
- Design and implement experimental protocols to evaluate the dynamometer’s performance
- Collect and analyse data to assess the reliability and accuracy of the dynamometer
- Document the study design, methods, results, and conclusions
Requirements:
- Solid python skills
- Solid knowledge in CAD is beneficial
- Experience with git is beneficial
- Ability to work independently and sound time management skills
Supervisor:
Charlotte Pradel, M.Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.
Python GUI Toolbox for Biosignal Data Analysis
We are looking for a Medical Engineering student for a 10 ECTS project to develop a Python-based GUI toolbox for EMG data analysis.
The project involves developing a Python (PySide6) GUI toolbox for interactive biosignal data analysis. The tool will support GUI-controlled signal processing, feature extraction, flexible plotting, label visualization, and exploratory analysis, enabling users to experiment with different methods and parameters.
Requirements:
- Strong Python programming skills
- Experience with Python GUI development (PySide6 / PyQt)
- Familiarity with scientific Python tools (NumPy, SciPy, Matplotlib)
- Interest in biosignal processing and data analysis
- Git experience is beneficial
- Ability to work independently
Supervisor:
Annika Ritter, M.Sc.
Amin Olamazadeh, M.Sc.
Application:
Please provide a short CV and transcript of records to nsquared@fau.de.