Fraunhofer IAOHere you will find a selection of exciting projects in which you can actively participate as part of a Master's, Bachelor's or student research project. Each project offers you the opportunity to gain valuable practical experience and further develop your expertise. If you are interested in one of the projects, please do not hesitate to contact us. We look forward to receiving your application and to working together on innovative research ideas!
| Projekttitel | Beschreibung | Details |
| Implementation of an application for the creation and administration of questionnaires for studies in the NeuroLab. | Questionnaires are common tools for collecting subjective data from participants. Filling them out digitally not only saves paper but also time that would otherwise be spent manually entering the data later. The task is to develop an app that allows researchers to assemble questionnaires as needed, use them in a study, and access the data digitally. This project is ideal for students interested in developing simple apps | Topic description |
| Linking Neural and Subjective Data of Human-Robot Interactions | This data analysis project focuses on correlating electroencephalography (EEG) data with subjective reports collected during an experiment on human-robot interaction. The objective is to identify patterns and relationships between the neural responses and the participants’ self-reported experiences, such as trust and comfort with the robot. The student will work with an existing dataset, applying statistical and machine learning techniques to analyze the data. The project aims to provide insights into how subjective experiences are reflected in neural activity, ultimately contributing to the improvement of human-robot interaction models. This project is ideal for students with a strong background in data analysis, neuroscience, and psychology, and an interest in the intersection of human-robot interaction and cognitive science. | Topic description |
| Development of a VR video game that measures the player's brain data and classifies the player's mental state in order to influence the game environment. | MindTrain was one of the first games from the NeuroLab that measured the player's state of relaxation and concentration using electroencephalography (EEG) to influence the game environment. That was a few years ago, and in the meantime, more advanced technologies and concepts have been released. It's time for the MindTrain game to receive an update. Students have the opportunity to try out new hardware (EEG, VR headset, eye-tracker), implement new classification algorithms, or develop a new game that uses neurofeedback to passively influence the game. This project is ideal for students interested in Brain-Computer-Interfaces, Game development and machine learning. | Topic description |
| Mental Rotation in VR - Effects on Working Memory in Autists and Neurotypicals | This data analysis project investigates the effects of mental rotation tasks within a virtual reality (VR) environment on working memory performance in autistic individuals compared to neurotypicals. The study aims to explore whether the immersive nature of VR influences cognitive load and spatial working memory differently across these two groups. The student will analyze the dataset of a VR-based mental rotation experiment conducted in autists and neurotypicals during which reaction times and error rates were recorded. The analysis will involve statistical comparisons of behavioral data and a review of the current literature on mental rotation and spatial working memory task in VR, with focus on autism research. This project is ideal for students interested in psychology, VR technology, and autism research, particularly those with skills in data analysis and statistical methods. | Topic description |
| Developing a Live Heart Beat Monitoring Application for PowerPoint | This project involves the development of a real-time heartbeat monitoring application that integrates with Microsoft PowerPoint. The application will capture live heart rate data from a wearable device (e.g., smartwatch) and display the data dynamically within a PowerPoint presentation. The project requires the design and implementation of software that can interface with the wearable device using Lab Streaming Layer (LSL), process the data, and update an animation integrated in a PowerPoint slide in real-time. The application is intended to be used for presentations in health-related fields, live demonstrations, or interactive sessions. This project is ideal for students with skills in software development, particularly in integrating APIs, data processing, and PowerPoint automation. It is ideal for those interested in combining health technology with innovative presentation tools. | Topic description |
| Application of Layerwise Relevance Propagation to Classifiers for Neurophysiological Data | This project explores the use of Layerwise Relevance Propagation (LRP) to enhance the interpretability of classifiers applied to neurophysiological data, such as EEG or fNIRS signals. LRP is a technique that provides insights into how individual features contribute to a model's predictions, making it possible to understand which neural patterns are driving classification outcomes. The student will implement LRP on existing machine learning models trained on neurophysiological datasets, analyzing the results to identify key neural features associated with different cognitive or behavioral states. The project aims to bridge the gap between high-performance classifiers and their interpretability in the context of neurophysiological data analysis. This project is ideal for students with a background in machine learning, neuroinformatics, and computational neuroscience, especially those with experience in deep learning and neural data analysis. | Topic description |
| Measuring Arousal with Electrocardiography in Response to Vibro-tactile Stimulation: A Comparison Between Autists and Neurotypicals | This data analysis project aims to investigate the physiological arousal responses of autistic individuals compared to neurotypicals when exposed to vibro-tactile stimulation. Using electrocardiography (ECG) to measure heart rate and other related metrics, the project will assess differences in responses between the two groups. The student will analyze a dataset where participants were presented with vibro-tactile stimuli while their ECG data is recorded. The analysis will focus on comparing the arousal levels within and between participants, offering insights into processing of somatosensory stimuli. The project also includes a review of the current literature on ECG technology and autism research with focus on somatosensory stimuli. This project is ideal for students with interests in psychophysiology, cognitive neuroscience, and biomedical signal processing, particularly those with experience in data analysis and statistics. | Topic description |
| Building a Multiplayer Brain-Computer Interface Game Utilizing Eye-tracking and EEG | This student project involves the development of a multiplayer game that integrates braincomputer interface (BCI) technology using both eye-tracking and electroencephalography (EEG) signals. The objective is to create a collaborative game where players can control game elements and interact with each other using their eye movements and brainwave patterns. The main task of the student will be designing and implementing a screen-based game using Python and/or Unity that allows for controlling some game elements via neurophysiological signal input. The game is finally tested in a small proof-of-concept study. The project also includes a review of existing BCI technologies, eye-tracking systems, and EEG applications in gaming. This project is ideal for students interested in neurotechnology, game design, and human-computer interaction, with strong programming skills and an interest in BCI systems. | Topic description |
| Using Error-related Potentials to Train Voice Recognition in a Human-Robot Interaction Setting | This student project focuses on leveraging error-related potentials (ErrPs) in EEG data to improve voice recognition systems in human-robot interaction (HRI). The goal is to test a paradigm where a robot can detect a specific user’s voice command from their neural responses to errors in voice recognition. The project will involve executing an experiment where participants are attempt to activate a robot by voice recognition, collecting EEG data to capture ErrPs when voice recognition errors occur, and using this data to refine the robot's voice recognition model. The outcome is expected to enhance the robot's ability to adapt to individual users, leading to more natural and effective interactions. This project is well-suited for students with an interest in neurotechnology, machine learning, and robotics, particularly those with skills in signal processing and programming. | Topic description |
| Conducting an eye-tracking and EEG study to detect anomalies in traffic. | To detect anomalies in traffic, various annotations are presented in the footage to highlight them. This study examines which forms of annotation are most effective and whether participants can identify the category of wrong-way drivers. The task in this project is to conduct the study and collect the data. This project is ideal for students interested in neuropsychological research, study design and study execution. | Topic description |
| Measuring cognitive workload through event-related potentials in a gaming scenario. | Measuring cognitive workload in a gaming scenario oƯers many advantages. For example, difficulty levels can be optimally adjusted to individual players without them noticing, leading to a better gaming experience. Various studies have shown that through the use of different stimuli (auditory, tactile, or visual), so-called event-related potentials (ERPs) can be induced. These ERPs can be used to estimate cognitive workload. The task is to collect data in such a study using electroencephalography (EEG) and to analyze this data to investigate the diƯerences between various cognitive workloads. This project is ideal for students interested in mental state in gaming. | Topic description |
| Benchmarking Mobile EEG Devices to Lab Standard Gel-based EEG | This student project aims to evaluate the performance of mobile EEG devices in comparison to established lab-standard gel-based EEG systems. The project will involve conducting setting up a lab study to measure the accuracy, reliability, and usability of mobile EEG devices across various cognitive tasks. The student will collect data using both mobile and gel-based EEG systems, analyze the data for signal quality, and identify potential discrepancies between the two types of devices. The project also includes a review of the current literature on EEG technology and its applications, culminating in a comprehensive benchmarking report that could guide future developments in mobile EEG technology. This project is ideal for students interested in neurotechnology, biomedical engineering, or cognitive neuroscience, with skills in data analysis and an interest in the practical applications of EEG systems. | Topic description |
| Data analysis of an existing data set on the physical sensation of emotions | In this work, an existing data set will be analysed. The study dealt with the different perception of emotions between autistic and non-autistic people. Test subjects had to read various emotional stimuli and assess where on the body they felt the triggered emotions. The work is based on Nummenmaa (2013) https://www.pnas.org/doi/10.1073/pnas.1321664111. This project is ideal for students from the fields of psychology, data science or cognitive science. An understanding of statistics is required. | Topic description |
| Unsolicited application for your own project idea | We also welcome unsolicited applications with your own project ideas from students who are passionate about a particular topic that falls within our thematic focus areas. If you have innovative ideas and creative approaches that could enrich our research profile, we invite you to share your proposals with us. This project is ideal for students who want to show a high level of initiative and can work independently. | Topic suggestion |