Available thesis topics

Students interested in topics related to human-centered security and privacy have the opportunity to do their master theses / bachelor theses / practical research project (Einzelpraktikum) at the Research Institute CODE (Bundeswehr University Munich). More information on the research group on Usable Security and Privacy Group can be found on our website.

We offer a large variety of topics, including but not limited to:

• Public Security User Interfaces (Contact: Doruntina Murtezaj)
• Tangible Security/Privacy Mechanisms (Contact: Sarah Delgado)
• Human Behavior and Physiology in Security Contexts (Contact: Felix Dietz)
• Social Engineering and Phishing (Contact: Verena Distler)
• Behavioral Biometrics (Contact: Lukas Mecke)
• Physiologicacl Security (Contact: Mariam Hassib)
• Security and Privacy in Augmented Reality (Contact: oliver.hein ät unibw.de)

A list of current topics is available on our website.

If you are interested in working with us, please get in touch with the respective contact person.

Details

Description

Electrodermal activity (EDA) denotes the measurement of continuous changes in the electrical conductance properties of the skin in response to sweat secretion by the sweat glands. EDA is autonomously modulated by sympathetic nervous system (SNS) activity, a component of the autonomic nervous system (ANS), which is involved in the control of involuntary bodily functions as well as cognitive and emotional states. Specifically, phasic EDA activity correlated with stress, cognitive load, and attention orienting. Therefore, measuring phasic EDA responses can give us information about the user's state.In this thesis project, we want to develop an adaptive system that modifies the visual complexity of the VR environment based on changes in phasic EDA. Specifically, we want to use new signal processing methodologies termed adaptive thresholding and gaussian filtering.The research consists of three main stages: (1) validation of the psychophysiological inference underpinning the adaptive system (2) implementation of a working VR prototype, and (3) an evaluation of the adaptive environment.

You will

• Perform a literature review
• Modify an existing VR environment
• Implement an preprocessing pipeline for phasic EDA detection
• Collect and analyze electroencephalographic (EEG), electrodermal activity (EDA) and electrocardiography (ECG) data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, MNE).

References

• Fairclough, S. H. (2009). Fundamentals of physiological computing. Interacting with computers, 21(1-2), 133-145.
• Chiossi, F., Welsch, R., Villa, S., Chuang, L., & Mayer, S. (2022). Virtual Reality Adaptation Using Electrodermal Activity to Support the User Experience. Big Data and Cognitive Computing, 6(2), 55.
• Babaei, E., Tag, B., Dingler, T., & Velloso, E. (2021, May). A critique of electrodermal activity practices at chi. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (pp. 1-14).
• Kleckner, I., Wormwood, J. B., Jones, R. M., Siegel, E., Culakova, E., Heathers, J., ... & Goodwin, M. (2021). Adaptive thresholding increases ability to detect changes in rate of skin conductance responses to psychologically arousing stimuli.

Details

Description

Mixed reality (MR) systems refer to the entire broad spectrum that ranges from physical to virtual reality (VR). It includes instances that overlay virtual content on physical information, i.e., Augmented Reality (AR), and those that rely on physical content to increase the realism of virtual environments, i.e., Augmented Virtuality (AV). Such instances tend to be pre-defined for the blend of physical and virtual content. To what extent can MR systems rely on physiological inputs to infer user state and expectations and, in doing, adapt their visualization in response? Measurement sensors for eye and body motion, autonomic arousal (e.g., respiration, electrodermaland heart activity), and cortical activity (e.g., EEG, fNIRS) are widely used in psychological and neuroscience research to infer hidden user states, such as stress, overt/covert attention, working memory load, etc.However, it is unclear if such inferences can serve as useful real-time inputs in controlling the presentation parameters of MR environments.In this thesis project, we will investigate whether this blend can be adaptive to user states, which are inferred from physiological measurements derived from gaze behavior, peripheral physiology (e.g.., electrodermal activity (EDA); electrocardiography (ECG)), and cortical activity (i.e.., electroencephalography (EEG)). In other words, we will investigate the viability and usefulness of MR use scenarios that vary in their blend of virtual and physicalcontent according to user physiology. In particular, we will focus on understanding how physiological readings can passively determine the appropriate amount ofvisual information to present within an MR system.

You will

• Perform a literature review
• Modify an MR environment
• Adapt existing processing pipeline for EEG and EDA data
• Collect and analyze electroencephalographic (EEG), electrodermal activity (EDA), and electrocardiography (ECG) data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, Neurokit)

References

• Lotte, F., Faller, J., Guger, C., Renard, Y., Pfurtscheller, G., Lecuyer, A., & Leeb, R. (2012). Combining BCI with virtual reality: towards new applications and improved BCI. In Towards practical brain-computer interfaces (pp. 197-220). Springer, Berlin, Heidelberg.
• McGill, M., Boland, D., Murray-Smith, R., & Brewster, S. (2015, April). A dose of reality: Overcoming usability challenges in vr head-mounted displays. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 2143-2152).
• Fairclough, S. H. (2009). Fundamentals of physiological computing. Interacting with computers, 21(1-2), 133-145.

Details

Description

Biocybernetic adaptation is a form of physiological computing where real-time physiological data from the brain and the body can be used as an input to adapt the user interface. In this way, from the physiological data, we can infer the user’s state and design implicit interactions in VR to change the scene to support certain goals. This thesis aims the develop and evaluate an adaptive VR environment designed to maximize users' performance by exploiting changes in real-time electroencephalography (EEG) to adjust the level of visual complexity. The research consists of three main stages: (1) validation of the input EEG measures underpinning the loop; (2) implementation of a working VR prototype; and (3) an evaluation of the adaptive environment. Specifically, we aim to demonstrate the sensitivity of EEG power in the (frontal) theta and (parietal) alpha bands to adapt levels of visual complexity.

You will

• Perform a literature review
• Modify an existing VR environment
• Implement an online biocybernetic loop using EEG
• Collect and analyze EEG, EDA, and ECG data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity and/or C#
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, MNE).

References

• Biocybernetics Loops and Physiological Computing
• Development of an Adaptive Game using EEG frequencies

Details

Description

Research from cognitive science and computerized displays of simple stimuli has shown how perceptual load is a critical factor for modulating distraction. Perceptual load is the amount of information involved in processing task stimuli. According to Lavie (1995), our attentional resources are limited and mainly directed towards task-relevant goals, but we might be more prone to distractors if we have cognitive spare resources. Previous research showed that human faces have bigger distracting power than non-face objects. This project aims to assess the distracting potential distracting effect of human avatars in a social VR scenario. We aim to transfer of traditional paradigms that assess attention and distraction to immersive VR. Lastly, we adapt the target-distractor recognizability to evaluate if a physiologically-adaptive system that optimizes for perceptual load can support task performance. The research consists of three main stages: (1) validation of the psychophysiological inference underpinning the physiological loop (2) implementation of a working VR prototype, and (3) an evaluation of the adaptive environment.

You will

• Perform a literature review
• Modify an existing VR environment
• Implement an online biocybernetic loop using EEG and/or EDA
• Collect and analyze electroencephalography (EEG), electrodermal activity (EDA), and electrocardiography (ECG) data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity and/or C#
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, Neurokit, MNE).

References

• Perceptual Load of faces
• Perceptual load and task engagement
• Evaluating perceptual load in VR

Details

Description

Physiological computing is a multidisciplinary research field in HCI wherein the interaction depends on measuring and responding to the user's physiological activity in real-time (Fairclough, 2009). Physiological computing allows for implicit interaction; by monitoring the physiological signals of the user, the computer can infer, e.g., if the task demands are either too challenging or easy, and either adapt the difficulty level or when users are getting distracted from the task, the system could give them a notification. Measuring the psychological state of the user creates intriguing possibilities for Social VR scenarios as we can either adapt the number of displayed avatars, their form or even their proxemic distance. This thesis aims the develop an adaptive Social VR environment designed to support users' performance when engaged in a cognitive task using a measure of physiological state (electrodermal activity: EDA) as input for adaptation. The research consists of three main stages: (1) validation of the psychophysiological inference underpinning the physiological loop (2) implementation of a working VR prototype, and (3) an evaluation of the adaptive environment.

You will

• Perform a literature review
• Modify an existing VR environment
• Implement an online biocybernetic loop using EDA
• Collect and analyze EEG, electrodermal activity (EDA) and electrocardiography (ECG) data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, Neurokit).

References

• Biocybernetics Loops and Physiological Computing
• Adapting task complexity of a Social VR environment based on skin conductance

Details

Description

Prior work has explored transition visualizations between VR environments, or on specific interaction techniques for transferring objects from VR <-> AR views. However, there has been less attention on what are the more effective transitions across the reality-virtuality continuum. The focus of this work would be to (a) identify suitable MR transitions (b) create a mapping to common tasks where such transitions may be applicable (e.g., keyboard typing) (c) prototype different transitions, from R-->AR-->AV--VR, and vice versa: VR-->AV-->AR--R, and empirically investigating different parameters of each (d) run a user evaluation to assess perceived UX. comfort, sickness, etc. This project extends the work in Keep it simple? Evaluation of Transitions VR, by exploring MR transitions, instead of only across different VR environments. Evaluation metrics will involve both objective and subjective measures.

RQ1: What are the most effective methods for transitioning users across the reality-virtuality spectrum?

RQ2: How do these transition visualizations influence user experience, user physiological state, workload, and acceptance across tasks?

You will

• Perform a literature review
• Develop a environment
• Implement an preprocessing pipeline for phasic EDA detection
• Collect and analyze electroencephalographic (EEG), electrodermal activity (EDA) and electrocardiography (ECG) data
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity
• Good knowledge of Python libraries for scientific computing (e.g. Scipy, MNE).
• Knowledge of physiological sensing

References

• Nico Feld, Pauline Bimberg, Benjamin Weyers, and Daniel Zielasko. 2023. Keep it simple? Evaluation of Transitions in Virtual Reality. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA '23). Association for Computing Machinery, New York, NY, USA, Article 196, 1-7. https://doi.org/10.1145/3544549.3585811
• Dimitar Valkov and Steffen Flagge. 2017. Smooth immersion: the benefits of making the transition to virtual environments a continuous process. In Proceedings of the 5th Symposium on Spatial User Interaction (SUI '17). Association for Computing Machinery, New York, NY, USA, 12-19. https://doi.org/10.1145/3131277.3132183
• Han, Jihae, Robbe Cools, and Adalberto L. Simeone. "The Body in Cross-Reality: A Framework for Selective Augmented Reality Visualisation of Virtual Objects." In XR@ ISS. 2020. https://ceur-ws.org/Vol-2779/paper6.pdf
• Cools, R., Esteves, A., & Simeone, A. L. (2022, October). Blending spaces: Cross-reality interaction techniques for object transitions between distinct virtual and augmented realities. In 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (pp. 528-537). IEEE.
• Pointecker, F., Friedl, J., Schwajda, D., Jetter, H.C. and Anthes, C., 2022, October. Bridging the gap across realities: Visual transitions between virtual and augmented reality. In 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) (pp. 827-836). IEEE.
• Uwe Gruenefeld, Jonas Auda, Florian Mathis, Stefan Schneegass, Mohamed Khamis, Jan Gugenheimer, and Sven Mayer. 2022. VRception: Rapid Prototyping of Cross-Reality Systems in Virtual Reality. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 611, 1-15. https://doi.org/10.1145/3491102.3501821

Details

Description

Project Overview
This thesis project presents a unique opportunity for students to contribute to innovative research on adaptive RSVP (Rapid Serial Visual Presentation) systems, following up from [1]. The focus is on developing an intelligent RSVP system that adapts to user attention and cognitive load by leveraging pupil dilation data. Pupil dilation has been shown to correlate with cognitive processing, providing valuable insight into the user's mental state while reading or processing visual stimuli. By incorporating this biometric feedback into the RSVP system, the project aims to create a more intuitive and personalized reading experience, especially for users with attention challenges or disabilities.

Project Motivation

Traditional RSVP systems often rely on fixed speeds or manual adjustments, which may not suit every user's cognitive capacity. This project seeks to enhance user engagement and efficiency by using real-time pupil dilation data to adjust the speed and presentation style dynamically. By doing so, the RSVP system can become more responsive to individual reading habits, reducing cognitive overload and improving comprehension and retention of information. This work has important implications for accessibility, enabling better interaction for users with reading difficulties or neurological impairments.

Project Goals

This thesis will explore the development and evaluation of an adaptive RSVP system, with a focus on the following key objectives:

• Experiment Design: Participants will engage with an RSVP system where reading speeds are adjusted in real-time based on pupil dilation data, providing insights into the correlation between cognitive load and visual presentation speed.
• Model Development: Develop a model that interprets pupil dilation changes and optimizes the RSVP presentation in response to varying cognitive loads, ensuring that reading pace and comprehension are maximized.

You will

• Conduct a literature review on pupil dilation and cognitive load in relation to visual stimuli
• Develop or modify an RSVP system to integrate real-time pupil tracking data
• Implement a preprocessing pipeline to analyze pupil dilation data during RSVP tasks
• Collect and analyze data, focusing on how pupil dilation correlates with reading performance and user engagement
• Summarize findings in a thesis and present them to an audience
• (Optional) Co-write a research paper based on the results

You need

• Strong communication skills in English
• Experience with eye-tracking technologies and software
• Basic knowledge of machine learning for modeling data (e.g., Python, TensorFlow)

References

• [1] Grootjen, J., Thalhammer, P., & Kosch, T. (2024). Your eyes on speed: Using pupil dilation to adaptively select speed-reading parameters in virtual reality. In Proceedings of the 26th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '24). ACM. https://doi.org/10.1145/3676531

Details

Description

Project OverviewThis thesis project offers an exciting opportunity for students to contribute to cutting-edge research on gaze estimation in interactive systems. The focus is on enhancing the accuracy of gaze interpretation within Collaborative Virtual Environments (CVEs), where effective communication is often dependent on understanding where participants are looking. Gaze serves as a vital non-verbal communication cue, yet people frequently struggle to accurately determine another persons gaze direction (i.e., where someone is looking), especially over distances.

Project Motivation

In CVEs, precise gaze estimation is crucial for natural and effective interaction. While previous research has explored distant pointing as an interaction mechanism, this project shifts focus to gaze estimation. By addressing common inaccuracies in gaze prediction, this research aims to significantly improve how users interpret each others gaze during virtual interactions, ultimately enhancing the overall immersive experience.

Project Goals

This thesis will investigate how accurately gaze estimation can be performed in CVEs, focusing on two main aspects:

• 1. Gaze Estimation Experiments: Participants will perform gaze tasks directed at targets on a screen from two different distances. The data collected will help evaluate the performance of current gaze estimation methods in these scenarios.
• 2. Model Development: Using the insights from distant pointing research, the project aims to develop a mathematical model to correct (potential) systematic displacements in gaze estimation.

You will

• Perform a literature review
• Modify an existing VR environment
• Implement an preprocessing pipeline for eye-tracking data
• Collect and analyze eye-tracking data, focussing on developing a model to correct potential systematic displacement in gaze estimation
• Summarize your findings in a thesis and present them to an audience
• (Optional) co-writing a research paper

You need

• Strong communication skills in English
• Good knowledge of Unity

References

• [1] Schweigert, R., Schwind, V., & Mayer, S. (2019). EyePointing: A gaze-based selection technique. In Proceedings of Mensch und Computer 2019. ACM. https://doi.org/10.1145/3340764.3344897
• [2] Mayer, S., Schwind, V., Schweigert, R., & Henze, N. (2018). The effect of offset correction and cursor on mid-air pointing in real and virtual environments. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 653:1–653:13). ACM. https://doi.org/10.1145/3173574.3174227
• [3] Mayer, S., Wolf, K., Schneegass, S., & Henze, N. (2015). Modeling distant pointing for compensating systematic displacements. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 4165–4168). ACM. https://doi.org/10.1145/2702123.2702332

Details

As technology advances, it becomes increasingly important to assess how humans perceive and respond to empathy from digital interfaces and devices. The "Perceived Empathy of Technology Scale" is a tool used to measure how empathetically users experience these interactions. However, this scale is currently only available in English, limiting research to English-speaking populations. With a German translation, researchers can more effectively evaluate perceptions of empathy in technology among German-speaking users, expanding the scale’s reach and supporting cross-cultural research on empathy in human-technology interaction.

You will:

• Conduct a literature review on empathy perception in human-technology interaction, including tools for measuring empathy.
• Translate the "Perceived Empathy of Technology Scale" into German using a forward-backward translation approach to ensure accuracy.
• Collaborate with two independent translators to create an initial translation, then consolidate the versions into one.
• Back-translate the consolidated version with a new set of translators to verify consistency with the original English version.
• Consult domain experts in psychology and human-technology interaction to review the translated scale for cultural relevance and content accuracy.
• Conduct a pilot test with a small sample of German-speaking participants to detect issues like misunderstandings or ambiguities in wording.
• Perform psychometric validation of the final German version, including Confirmatory Factor Analysis, Criterion Validity, and Measurement Invariance Analysis.
• Summarize your findings in a thesis and present them.
• (Optional) Co-author a research paper based on your findings.

You need:

• Strong communication skills in German and English
• Understanding of psychometric evaluation and analysis
• (Optional) Prior experience in translation and back-translation processes
• Fundamental skills in statistical analysis software (e.g., R)

Details

Description

Neurotechnology has been typically used in the medical domain. However, they can bring huge benefits to healthy individuals as well. In this thesis, we will use transcranial direct stimulation in a controlled environment to test inhibition control in individuals (how good is a person at stopping an instinctive action). You will conduct a series of user studies following an established protocol and analyze whether transcranial stimulation helps participant inhibition. This work moves forward the field of human-computer interaction to enhance human capabilities.

You will

• Perform a review of current literature
• Collect data in a lab experiment
• Learn how to stimulate the brain using medical grade devices

You need

• User Study Experience
• Good communication skills

References

• Steeven Villa, Jasmin Niess, Takuro Nakao, Jonathan Lazar, Albrecht Schmidt, and Tonja-Katrin Machulla. 2023. Understanding Perception of Human Augmentation: A Mixed-Method Study.
• Albrecht Schmidt Augmenting Human Intellect and Amplifying Perception and Cognition

Details