Dr. Uwe Grünefeld

Wissenschaftlicher Assistent

Dr. Uwe Grünefeld

S-M 203
+49 201 18-33298
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Universität Duisburg-Essen
Institut für Informatik und Wirtschaftsinformatik (ICB)
Mensch-Computer Interaktion
Schützenbahn 70
45127 Essen
Google Scholar


  • Pascher, Max; Saad, Alia; Liebers, Jonathan; Heger, Roman; Gerken, Jens; Schneegass, Stefan; Gruenefeld, Uwe: Hands-On Robotics: Enabling Communication Through Direct Gesture Control. In: Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI '24 Companion), March 11--14, 2024, Boulder, CO, USA. ACM, Boulder, Colorado, USA 2024. doi:10.1145/3610978.3640635PDFBIB DownloadDetails
    Hands-On Robotics: Enabling Communication Through Direct Gesture Control

    Effective Human-Robot Interaction (HRI) is fundamental to seamlessly integrating robotic systems into our daily lives. However, current communication modes require additional technological interfaces, which can be cumbersome and indirect. This paper presents a novel approach, using direct motion-based communication by moving a robot's end effector. Our strategy enables users to communicate with a robot by using four distinct gestures -- two handshakes ('formal' and 'informal') and two letters ('W' and 'S'). As a proof-of-concept, we conducted a user study with 16 participants, capturing subjective experience ratings and objective data for training machine learning classifiers. Our findings show that the four different gestures performed by moving the robot's end effector can be distinguished with close to 100% accuracy. Our research offers implications for the design of future HRI interfaces, suggesting that motion-based interaction can empower human operators to communicate directly with robots, removing the necessity for additional hardware.

  • Liebers, Carina; Pfützenreuter, Niklas; Auda, Jonas; Gruenefeld, Uwe; Schneegass, Stefan: "Computer, Generate!” – Investigating User Controlled Generation of Immersive Virtual Environments. In: HHAI 2024: Hybrid Human AI Systems for the Social Good. IOS Press, Malmö 2024, S. 213-227. doi:10.3233/FAIA240196PDFVolltextBIB DownloadDetails

    For immersive experiences such as virtual reality, explorable worlds are often fundamental. Generative artificial intelligence looks promising to accelerate the creation of such environments. However, it remains unclear how existing interaction modalities can support user-centered world generation and how users remain in control of the process. Thus, in this paper, we present a virtual reality application to generate virtual environments and compare three common interaction modalities (voice, controller, and hands) in a pre-study (N = 18), revealing a combination of initial voice input and continued controller manipulation as best suitable. We then investigate three levels of process control (all-at-once, creation-before-manipulation, and step-by-step) in a user study (N = 27). Our results show that although all-at-once reduced the number of object manipulations, participants felt more in control when using the step-by-step approach.

  • Liebers, Carina; Pfützenreuter, Niklas; Prochazka, Marvin; Megarajan, Pranav; Furuno, Eike; Löber, Jan; Stratmann, Tim C.; Auda, Jonas; Degraen, Donald; Gruenefeld, Uwe; Schneegass, Stefan: Look Over Here! Comparing Interaction Methods for User-Assisted Remote Scene Reconstruction. In: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA 2024. doi:10.1145/3613905.3650982PDFBIB DownloadDetails

    Detailed digital representations of physical scenes are key in many cases, such as historical site preservation or hazardous area inspection. To automate the capturing process, robots or drones mounted with sensors can algorithmically record the environment from different viewpoints. However, environmental complexities often lead to incomplete captures. We believe humans can support scene capture as their contextual understanding enables easy identification of missing areas and recording errors. Therefore, they need to perceive the recordings and suggest new sensor poses. In this work, we compare two human-centric approaches in Virtual Reality for scene reconstruction through the teleoperation of a remote robot arm, i.e., directly providing sensor poses (direct method) or specifying missing areas in the scans (indirect method). Our results show that directly providing sensor poses leads to higher efficiency and user experience. In future work, we aim to compare the quality of human assistance to automatic approaches.

  • Liebers, Carina; Megarajan, Pranav; Auda, Jonas; Stratmann, Tim C; Pfingsthorn, Max; Gruenefeld, Uwe; Schneegass, Stefan: Keep the Human in the Loop: Arguments for Human Assistance in the Synthesis of Simulation Data for Robot Training. In: Multimodal Technologies and Interaction, Jg. 8 (2024), S. 18. doi:10.3390/mti8030018PDFVolltextBIB DownloadDetails
    Keep the Human in the Loop: Arguments for Human Assistance in the Synthesis of Simulation Data for Robot Training

    Robot training often takes place in simulated environments, particularly with reinforcement learning. Therefore, multiple training environments are generated using domain randomization to ensure transferability to real-world applications and compensate for unknown real-world states. We propose improving domain randomization by involving human application experts in various stages of the training process. Experts can provide valuable judgments on simulation realism, identify missing properties, and verify robot execution. Our human-in-the-loop workflow describes how they can enhance the process in five stages: validating and improving real-world scans, correcting virtual representations, specifying application-specific object properties, verifying and influencing simulation environment generation, and verifying robot training. We outline examples and highlight research opportunities. Furthermore, we present a case study in which we implemented different prototypes, demonstrating the potential of human experts in the given stages. Our early insights indicate that human input can benefit robot training at different stages.

  • Saad, Alia; Pascher, Max; Kassem, Khaled; Heger, Roman; Liebers, Jonathan; Schneegass, Stefan; Gruenefeld, Uwe: Hand-in-Hand: Investigating Mechanical Tracking for User Identification in Cobot Interaction. In: Proceedings of International Conference on Mobile and Ubiquitous Multimedia (MUM). Vienna, Austria 2023. doi:10.1145/3626705.3627771PDFBIB DownloadDetails
    Hand-in-Hand: Investigating Mechanical Tracking for User Identification in Cobot Interaction

    Robots play a vital role in modern automation, with applications in manufacturing and healthcare. Collaborative robots integrate human and robot movements. Therefore, it is essential to ensure that interactions involve qualified, and thus identified, individuals. This study delves into a new approach: identifying individuals through robot arm movements. Different from previous methods, users guide the robot, and the robot senses the movements via joint sensors. We asked 18 participants to perform six gestures, revealing the potential use as unique behavioral traits or biometrics, achieving F1-score up to 0.87, which suggests direct robot interactions as a promising avenue for implicit and explicit user identification.

  • Auda, Jonas; Grünefeld, Uwe; Faltaous, Sarah; Mayer, Sven; Schneegass, Stefan: A Scoping Survey on Cross-reality Systems. In: ACM Computing Surveys. 2023. doi:10.1145/3616536BIB DownloadDetails
    A Scoping Survey on Cross-reality Systems

    Immersive technologies such as Virtual Reality (VR) and Augmented Reality (AR) empower users to experience digital realities. Known as distinct technology classes, the lines between them are becoming increasingly blurry with recent technological advancements. New systems enable users to interact across technology classes or transition between them—referred to as cross-reality systems. Nevertheless, these systems are not well understood. Hence, in this article, we conducted a scoping literature review to classify and analyze cross-reality systems proposed in previous work. First, we define these systems by distinguishing three different types. Thereafter, we compile a literature corpus of 306 relevant publications, analyze the proposed systems, and present a comprehensive classification, including research topics, involved environments, and transition types. Based on the gathered literature, we extract nine guiding principles that can inform the development of cross-reality systems. We conclude with research challenges and opportunities.

  • Auda, Jonas; Grünefeld, Uwe; Mayer, Sven; Faltaous, Sarah; Schneegass, Stefan: The Actuality-Time Continuum: Visualizing Interactions and Transitions Taking Place in Cross-Reality Systems. In: IEEE ISMAR 2023. Sydney 2023. VolltextBIB DownloadDetails
    The Actuality-Time Continuum: Visualizing Interactions and Transitions Taking Place in Cross-Reality Systems

    In the last decade, researchers contributed an increasing number of cross-reality systems and their evaluations. Going beyond individual technologies such as Virtual or Augmented Reality, these systems introduce novel approaches that help to solve relevant problems such as the integration of bystanders or physical objects. However, cross-reality systems are complex by nature, and describing the interactions and transitions taking place is a challenging task. Thus, in this paper, we propose the idea of the Actuality-Time Continuum that aims to enable researchers and designers alike to visualize complex cross-reality experiences. Moreover, we present four visualization examples that illustrate the potential of our proposal and conclude with an outlook on future perspectives.

  • Keppel, Jonas; Strauss, Marvin; Faltaous, Sarah; Liebers, Jonathan; Heger, Roman; Gruenefeld, Uwe; Schneegass, Stefan: Don't Forget to Disinfect: Understanding Technology-Supported Hand Disinfection Stations. In: Proc. ACM Hum.-Comput. Interact., Jg. 7 (2023). doi:10.1145/3604251PDFBIB DownloadDetails
    Don't Forget to Disinfect: Understanding Technology-Supported Hand Disinfection Stations

    The global COVID-19 pandemic created a constant need for hand disinfection. While it is still essential, disinfection use is declining with the decrease in perceived personal risk (e.g., as a result of vaccination). Thus this work explores using different visual cues to act as reminders for hand disinfection. We investigated different public display designs using (1) paper-based only, adding (2) screen-based, or (3) projection-based visual cues. To gain insights into these designs, we conducted semi-structured interviews with passersby (N=30). Our results show that the screen- and projection-based conditions were perceived as more engaging. Furthermore, we conclude that the disinfection process consists of four steps that can be supported: drawing attention to the disinfection station, supporting the (subconscious) understanding of the interaction, motivating hand disinfection, and performing the action itself. We conclude with design implications for technology-supported disinfection.

  • Pascher, Max; Grünefeld, Uwe; Schneegass, Stefan; Gerken, Jens: How to Communicate Robot Motion Intent: A Scoping Review. In: Acm (Hrsg.): Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23). 2023. doi:10.1145/3544548.3580857PDFVolltextBIB DownloadDetails
    How to Communicate Robot Motion Intent: A Scoping Review

    Robots are becoming increasingly omnipresent in our daily lives, supporting us and carrying out autonomous tasks. In Human-Robot Interaction, human actors benefit from understanding the robot's motion intent to avoid task failures and foster collaboration. Finding effective ways to communicate this intent to users has recently received increased research interest. However, no common language has been established to systematize robot motion intent. This work presents a scoping review aimed at unifying existing knowledge. Based on our analysis, we present an intent communication model that depicts the relationship between robot and human through different intent dimensions (intent type, intent information, intent location). We discuss these different intent dimensions and their interrelationships with different kinds of robots and human roles. Throughout our analysis, we classify the existing research literature along our intent communication model, allowing us to identify key patterns and possible directions for future research.

  • Pascher, Max; Franzen, Til; Kronhardt, Kirill; Grünefeld, Uwe; Schneegass, Stefan; Gerken, Jens: HaptiX: Vibrotactile Haptic Feedback for Communication of 3D Directional Cues. In: Acm (Hrsg.): Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems - Extended Abstract (CHI ’23). 2023. doi:10.1145/3544549.3585601PDFVolltextBIB DownloadDetails
    HaptiX: Vibrotactile Haptic Feedback for Communication of 3D Directional Cues

    In Human-Computer-Interaction, vibrotactile haptic feedback offers the advantage of being independent of any visual perception of the environment. Most importantly, the user's field of view is not obscured by user interface elements, and the visual sense is not unnecessarily strained. This is especially advantageous when the visual channel is already busy, or the visual sense is limited. We developed three design variants based on different vibrotactile illusions to communicate 3D directional cues. In particular, we explored two variants based on the vibrotactile illusion of the cutaneous rabbit and one based on apparent vibrotactile motion. To communicate gradient information, we combined these with pulse-based and intensity-based mapping. A subsequent study showed that the pulse-based variants based on the vibrotactile illusion of the cutaneous rabbit are suitable for communicating both directional and gradient characteristics. The results further show that a representation of 3D directions via vibrations can be effective and beneficial.

  • Keppel, Jonas; Gruenefeld, Uwe; Strauss, Marvin; Gonzalez, Luis Ignacio Lopera; Amft, Oliver; Schneegass, Stefan: Reflecting on Approaches to Monitor User's Dietary Intake, MobileHCI 2022, Vancouver, Canada 2022. PDFVolltextBIB DownloadDetails

    Monitoring dietary intake is essential to providing user feedback and achieving a healthier lifestyle. In the past, different approaches for monitoring dietary behavior have been proposed. In this position paper, we first present an overview of the state-of-the-art techniques grouped by image- and sensor-based approaches. After that, we introduce a case study in which we present a Wizard-of-Oz approach as an alternative and non-automatic monitoring method.

  • Detjen, Henrik; Faltaous, Sarah; Keppel, Jonas; Prochazka, Marvin; Gruenefeld, Uwe; Sadeghian, Shadan; Schneegass, Stefan: Investigating the Influence of Gaze- and Context-Adaptive Head-up Displays on Take-Over Requests. In: Acm (Hrsg.): AutomotiveUI '22: Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 2022. doi:10.1145/3543174.3546089VolltextBIB DownloadDetails

    In Level 3 automated vehicles, preparing drivers for take-over requests (TORs) on the head-up display (HUD) requires their repeated attention. Visually salient HUD elements can distract attention from potentially critical parts in a driving scene during a TOR. Further, attention is (a) meanwhile needed for non-driving-related activities and can (b) be over-requested. In this paper, we conduct a driving simulator study (N=12), varying required attention by HUD warning presence (absent vs. constant vs. TOR-only) across gaze-adaptivity (with vs. without) to fit warnings to the situation. We found that (1) drivers value visual support during TORs, (2) gaze-adaptive scene complexity reduction works but creates a benefit-neutralizing distraction for some, and (3) drivers perceive constant HUD warnings as annoying and distracting over time. Our findings highlight the need for (a) HUD adaptation based on user activities and potential TORs and (b) sparse use of warning cues in future HUD designs.

  • Faltaous, Sarah; Prochazka, Marvin; Auda, Jonas; Keppel, Jonas; Wittig, Nick; Gruenefeld, Uwe; Schneegass, Stefan: Give Weight to VR: Manipulating Users’ Perception of Weight in Virtual Reality with Electric Muscle Stimulation, Association for Computing Machinery, New York, NY, USA 2022. (ISBN 9781450396905) doi:10.1145/3543758.3547571) BIB DownloadDetails

    Virtual Reality (VR) devices empower users to experience virtual worlds through rich visual and auditory sensations. However, believable haptic feedback that communicates the physical properties of virtual objects, such as their weight, is still unsolved in VR. The current trend towards hand tracking-based interactions, neglecting the typical controllers, further amplifies this problem. Hence, in this work, we investigate the combination of passive haptics and electric muscle stimulation to manipulate users’ perception of weight, and thus, simulate objects with different weights. In a laboratory user study, we investigate four differing electrode placements, stimulating different muscles, to determine which muscle results in the most potent perception of weight with the highest comfort. We found that actuating the biceps brachii or the triceps brachii muscles increased the weight perception of the users. Our findings lay the foundation for future investigations on weight perception in VR.

  • Grünefeld, Uwe; Geilen, Alexander; Liebers, Jonathan; Wittig, Nick; Koelle, Marion; Schneegass, Stefan: ARm Haptics: 3D-Printed Wearable Haptics for Mobile Augmented Reality. In: Proc. ACM Hum.-Comput. Interact., Jg. 6 (2022). doi:10.1145/3546728BIB DownloadDetails

    Augmented Reality (AR) technology enables users to superpose virtual content onto their environments. However, interacting with virtual content while mobile often requires users to perform interactions in mid-air, resulting in a lack of haptic feedback. Hence, in this work, we present the ARm Haptics system, which is worn on the user's forearm and provides 3D-printed input modules, each representing well-known interaction components such as buttons, sliders, and rotary knobs. These modules can be changed quickly, thus allowing users to adapt them to their current use case. After an iterative development of our system, which involved a focus group with HCI researchers, we conducted a user study to compare the ARm Haptics system to hand-tracking-based interaction in mid-air (baseline). Our findings show that using our system results in significantly lower error rates for slider and rotary input. Moreover, use of the ARm Haptics system results in significantly higher pragmatic quality and lower effort, frustration, and physical demand. Following our findings, we discuss opportunities for haptics worn on the forearm.

  • Grünefeld, Uwe; Auda, Jonas; Mathis, Florian; Schneegass, Stefan; Khamis, Mohamed; Gugenheimer, Jan; Mayer, Sven: VRception: Rapid Prototyping of Cross-Reality Systems in Virtual Reality. In: Proceedings of the 41st ACM Conference on Human Factors in Computing Systems (CHI). Association for Computing Machinery, New Orleans, United States 2022. doi:10.1145/3491102.3501821BIB DownloadDetails

    Cross-reality systems empower users to transition along the realityvirtuality continuum or collaborate with others experiencing different manifestations of it. However, prototyping these systems is challenging, as it requires sophisticated technical skills, time, and often expensive hardware. We present VRception, a concept and toolkit for quick and easy prototyping of cross-reality systems. By simulating all levels of the reality-virtuality continuum entirely in Virtual Reality, our concept overcomes the asynchronicity of realities, eliminating technical obstacles. Our VRception Toolkit leverages this concept to allow rapid prototyping of cross-reality systems and easy remixing of elements from all continuum levels. We replicated six cross-reality papers using our toolkit and presented them to their authors. Interviews with them revealed that our toolkit sufficiently replicates their core functionalities and allows quick iterations. Additionally, remote participants used our toolkit in pairs to collaboratively implement prototypes in about eight minutes that they would have otherwise expected to take days.

  • Auda, Jonas; Grünefeld, Uwe; Schneegass, Stefan: If The Map Fits! Exploring Minimaps as Distractors from Non-Euclidean Spaces in Virtual Reality. In: CHI 22. ACM, 2022. doi:10.1145/3491101.3519621BIB DownloadDetails
  • Abdrabou, Yasmeen; Rivu, Radiah; Ammar, Tarek; Liebers, Jonathan; Saad, Alia; Liebers, Carina; Gruenefeld, Uwe; Knierim, Pascal; Khamis, Mohamed; Mäkelä, Ville; Schneegass, Stefan; Alt, Florian: Understanding Shoulder Surfer Behavior Using Virtual Reality. In: Proceedings of the IEEE conference on Virtual Reality and 3D User Interfaces (IEEE VR). IEEE, Christchurch, New Zealand 2022. BIB DownloadDetails

    We explore how attackers behave during shoulder surfing. Unfortunately, such behavior is challenging to study as it is often opportunistic and can occur wherever potential attackers can observe other people’s private screens. Therefore, we investigate shoulder surfing using virtual reality (VR). We recruited 24 participants and observed their behavior in two virtual waiting scenarios: at a bus stop and in an open office space. In both scenarios, avatars interacted with private screens displaying different content, thus providing opportunities for shoulder surfing. From the results, we derive an understanding of factors influencing shoulder surfing behavior.

  • Auda, Jonas; Grünefeld, Uwe; Kosch, Thomas; Schneegass, Stefan: The Butterfly Effect: Novel Opportunities for Steady-State Visually-Evoked Potential Stimuli in Virtual Reality. In: Researchgate (Hrsg.): Augmented Humans. Kashiwa, Chiba, Japan 2022. doi:10.1145/3519391.3519397BIB DownloadDetails
  • Pascher, Max; Kronhardt, Kirill; Franzen, Til; Gruenefeld, Uwe; Schneegass, Stefan; Gerken, Jens: My Caregiver the Cobot: Comparing Visualization Techniques to Effectively Communicate Cobot Perception to People with Physical Impairments. In: MDPI Sensors, Jg. 22 (2022). doi:10.3390/s22030755VolltextBIB DownloadDetails

    Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they "see" the world. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. All of these communicate cobot perception by visually indicating which objects in the cobot's surrounding have been identified by their sensors. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. In a second remote experiment, we validated these findings with a broader non-specific user base. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. Overall, users prefer Line as a more straightforward visualization. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative.

  • Liebers, Jonathan; Brockel, Sascha; Gruenefeld, Uwe; Schneegass, Stefan: Identifying Users by Their Hand Tracking Data in Augmented and Virtual Reality. In: International Journal of Human–Computer Interaction (2022). doi:10.1080/10447318.2022.2120845PDFBIB DownloadDetails
    Identifying Users by Their Hand Tracking Data in Augmented and Virtual Reality

    Nowadays, Augmented and Virtual Reality devices are widely available and are often shared among users due to their high cost. Thus, distinguishing users to offer personalized experiences is essential. However, currently used explicit user authentication(e.g., entering a password) is tedious and vulnerable to attack. Therefore, this work investigates the feasibility of implicitly identifying users by their hand tracking data. In particular, we identify users by their uni- and bimanual finger behavior gathered from their interaction with eight different universal interface elements, such as buttons and sliders. In two sessions, we recorded the tracking data of 16 participants while they interacted with various interface elements in Augmented and Virtual Reality. We found that user identification is possible with up to 95 % accuracy across sessions using an explainable machine learning approach. We conclude our work by discussing differences between interface elements, and feature importance to provide implications for behavioral biometric systems.

  • Keppel, Jonas; Liebers, Jonathan; Auda, Jonas; Gruenefeld, Uwe; Schneegass, Stefan: ExplAInable Pixels: Investigating One-Pixel Attacks on Deep Learning Models with Explainable Visualizations. In: Proceedings of the 21st International Conference on Mobile and Ubiquitous Multimedia. Association for Computing Machinery, New York, NY, USA 2022, S. 231-242. doi:10.1145/3568444.3568469BIB DownloadDetails

    Nowadays, deep learning models enable numerous safety-critical applications, such as biometric authentication, medical diagnosis support, and self-driving cars. However, previous studies have frequently demonstrated that these models are attackable through slight modifications of their inputs, so-called adversarial attacks. Hence, researchers proposed investigating examples of these attacks with explainable artificial intelligence to understand them better. In this line, we developed an expert tool to explore adversarial attacks and defenses against them. To demonstrate the capabilities of our visualization tool, we worked with the publicly available CIFAR-10 dataset and generated one-pixel attacks. After that, we conducted an online evaluation with 16 experts. We found that our tool is usable and practical, providing evidence that it can support understanding, explaining, and preventing adversarial examples.

  • Liebers, Jonathan; Horn, Patrick; Burschik, Christian; Gruenefeld, Uwe; Schneegass, Stefan: Using Gaze Behavior and Head Orientation for Implicit Identification in Virtual Reality. In: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology (VRST). Association for Computing Machinery, Osaka, Japan 2021. doi:10.1145/3489849.3489880BIB DownloadDetails

    Identifying users of a Virtual Reality (VR) headset provides designers of VR content with the opportunity to adapt the user interface, set user-specific preferences, or adjust the level of difficulty either for games or training applications. While most identification methods currently rely on explicit input, implicit user identification is less disruptive and does not impact the immersion of the users. In this work, we introduce a biometric identification system that employs the user’s gaze behavior as a unique, individual characteristic. In particular, we focus on the user’s gaze behavior and head orientation while following a moving stimulus. We verify our approach in a user study. A hybrid post-hoc analysis results in an identification accuracy of up to 75% for an explainable machine learning algorithm and up to 100% for a deep learning approach. We conclude with discussing application scenarios in which our approach can be used to implicitly identify users.

  • Auda, Jonas; Grünefeld, Uwe; Pfeuffer, Ken; Rivu, Radiah; Florian, Alt; Schneegass, Stefan: I'm in Control! Transferring Object Ownership Between Remote Users with Haptic Props in Virtual Reality. In: Proceedings of the 9th ACM Symposium on Spatial User Interaction (SUI). Association for Computing Machinery, 2021. doi:10.1145/3485279.3485287BIB DownloadDetails
  • Saad, Alia; Liebers, Jonathan; Gruenefeld, Uwe; Alt, Florian; Schneegass, Stefan: Understanding Bystanders’ Tendency to Shoulder Surf Smartphones Using 360-Degree Videos in Virtual Reality. In: Proceedings of the 23rd International Conference on Mobile Human-Computer Interaction (MobileHCI). Association for Computing Machinery, Toulouse, France 2021. doi:10.1145/3447526.3472058BIB DownloadDetails

    Shoulder surfing is an omnipresent risk for smartphone users. However, investigating these attacks in the wild is difficult because of either privacy concerns, lack of consent, or the fact that asking for consent would influence people’s behavior (e.g., they could try to avoid looking at smartphones). Thus, we propose utilizing 360-degree videos in Virtual Reality (VR), recorded in staged real-life situations on public transport. Despite differences between perceiving videos in VR and experiencing real-world situations, we believe this approach to allow novel insights on observers’ tendency to shoulder surf another person’s phone authentication and interaction to be gained. By conducting a study (N=16), we demonstrate that a better understanding of shoulder surfers’ behavior can be obtained by analyzing gaze data during video watching and comparing it to post-hoc interview responses. On average, participants looked at the phone for about 11% of the time it was visible and could remember half of the applications used.

  • Auda, Jonas; Grünefeld, Uwe; Schneegass, Stefan: Enabling Reusable Haptic Props for Virtual Reality by Hand Displacement. In: Proceedings of the Conference on Mensch Und Computer (MuC). Association for Computing Machinery, Ingolstadt, Germany 2021, S. 412-417. doi:10.1145/3473856.3474000BIB DownloadDetails

    Virtual Reality (VR) enables compelling visual experiences. However, providing haptic feedback is still challenging. Previous work suggests utilizing haptic props to overcome such limitations and presents evidence that props could function as a single haptic proxy for several virtual objects. In this work, we displace users’ hands to account for virtual objects that are smaller or larger. Hence, the used haptic prop can represent several differently-sized virtual objects. We conducted a user study (N = 12) and presented our participants with two tasks during which we continuously handed them the same haptic prop but they saw in VR differently-sized virtual objects. In the first task, we used a linear hand displacement and increased the size of the virtual object to understand when participants perceive a mismatch. In the second task, we compare the linear displacement to logarithmic and exponential displacements. We found that participants, on average, do not perceive the size mismatch for virtual objects up to 50% larger than the physical prop. However, we did not find any differences between the explored different displacement. We conclude our work with future research directions.

  • Faltaous, Sarah; Gruenefeld, Uwe; Schneegass, Stefan: Towards a Universal Human-Computer Interaction Model for Multimodal Interactions. In: Proceedings of the Conference on Mensch Und Computer (MuC). Association for Computing Machinery, Ingolstadt, Germany 2021, S. 59-63. doi:10.1145/3473856.3474008BIB DownloadDetails

    Models in HCI describe and provide insights into how humans use interactive technology. They are used by engineers, designers, and developers to understand and formalize the interaction process. At the same time, novel interaction paradigms arise constantly introducing new ways of how interactive technology can support humans. In this work, we look into how these paradigms can be described using the classical HCI model introduced by Schomaker in 1995. We extend this model by presenting new relations that would provide a better understanding of them. For this, we revisit the existing interaction paradigms and try to describe their interaction using this model. The goal of this work is to highlight the need to adapt the models to new interaction paradigms and spark discussion in the HCI community on this topic.

  • Faltaous, Sarah; Janzon, Simon; Heger, Roman; Strauss, Marvin; Golkar, Pedram; Viefhaus, Matteo; Prochazka, Marvin; Gruenefeld, Uwe; Schneegass, Stefan: Wisdom of the IoT Crowd: Envisioning a Smart Home-Based Nutritional Intake Monitoring System. In: Proceedings of the Conference on Mensch Und Computer (MuC). Association for Computing Machinery, Ingolstadt, Germany 2021, S. 568-573. doi:10.1145/3473856.3474009BIB DownloadDetails

    Obesity and overweight are two factors linked to various health problems that lead to death in the long run. Technological advancements have granted the chance to create smart interventions. These interventions could be operated by the Internet of Things (IoT) that connects different smart home and wearable devices, providing a large pool of data. In this work, we use IoT with different technologies to present an exemplary nutrition monitoring intake system. This system integrates the input from various devices to understand the users’ behavior better and provide recommendations accordingly. Furthermore, we report on a preliminary evaluation through semi-structured interviews with six participants. Their feedback highlights the system’s opportunities and challenges.

  • Auda, Jonas; Heger, Roman; Gruenefeld, Uwe; Schneegaß, Stefan: VRSketch: Investigating 2D Sketching in Virtual Reality with Different Levels of Hand and Pen Transparency. In: 18th International Conference on Human–Computer Interaction (INTERACT). Springer, Bari, Italy 2021, S. 195-211. doi:10.1007/978-3-030-85607-6_14BIB DownloadDetails

    Sketching is a vital step in design processes. While analog sketching on pen and paper is the defacto standard, Virtual Reality (VR) seems promising for improving the sketching experience. It provides myriads of new opportunities to express creative ideas. In contrast to reality, possible drawbacks of pen and paper drawing can be tackled by altering the virtual environment. In this work, we investigate how hand and pen transparency impacts users’ 2D sketching abilities. We conducted a lab study (N=20N=20) investigating different combinations of hand and pen transparency. Our results show that a more transparent pen helps one sketch more quickly, while a transparent hand slows down. Further, we found that transparency improves sketching accuracy while drawing in the direction that is occupied by the user’s hand.

  • Liebers, Jonathan; Abdelaziz, Mark; Mecke, Lukas; Saad, Alia; Auda, Jonas; Alt, Florian; Schneegaß, Stefan: Understanding User Identification in Virtual Reality Through Behavioral Biometrics and the Effect of Body Normalization. In: Proceedings of the 40th ACM Conference on Human Factors in Computing Systems (CHI). Association for Computing Machinery, Yokohama, Japan 2021. doi:10.1145/3411764.3445528BIB DownloadDetails

    Virtual Reality (VR) is becoming increasingly popular both in the entertainment and professional domains. Behavioral biometrics have recently been investigated as a means to continuously and implicitly identify users in VR. Applications in VR can specifically benefit from this, for example, to adapt virtual environments and user interfaces as well as to authenticate users. In this work, we conduct a lab study (N = 16) to explore how accurately users can be identified during two task-driven scenarios based on their spatial movement. We show that an identification accuracy of up to 90% is possible across sessions recorded on different days. Moreover, we investigate the role of users’ physiology in behavioral biometrics by virtually altering and normalizing their body proportions. We find that body normalization in general increases the identification rate, in some cases by up to 38%; hence, it improves the performance of identification systems.

  • Schultze, Sven; Gruenefeld, Uwe; Boll, Susanne: Demystifying Deep Learning: Developing and Evaluating a User-Centered Learning App for Beginners to Gain Practical Experience. In: i-com, Jg. 2020 (2021) Nr. 19. doi:10.1515/icom-2020-0023BIB DownloadDetails

    Deep Learning has revolutionized Machine Learning, enhancing our ability to solve complex computational problems. From image classification to speech recognition, the technology can be beneficial in a broad range of scenarios. However, the barrier to entry is quite high, especially when programming skills are missing. In this paper, we present the development of a learning application that is easy to use, yet powerful enough to solve practical Deep Learning problems. We followed the human-centered design approach and conducted a technical evaluation to identify solvable classification problems. Afterwards, we conducted an online user evaluation to gain insights on users’ experience with the app, and to understand positive as well as negative aspects of our implemented concept. Our results show that participants liked using the app and found it useful, especially for beginners. Nonetheless, future iterations of the learning app should step-wise include more features to support advancing users.

  • Illing, Jannike; Klinke, Philipp; Gruenefeld, Uwe; Pfingsthorn, Max; Heuten, Wilko: Time is money! Evaluating Augmented Reality Instructions for Time-Critical Assembly Tasks. In: 19th International Conference on Mobile and Ubiquitous Multimedia (MUM). Association for Computing Machinery, Essen, Germany 2020, S. 277-287. doi:10.1145/3428361.3428398BIB DownloadDetails

    Manual assembly tasks require workers to precisely assemble parts in 3D space. Often additional time pressure increases the complexity of these tasks even further (e.g., adhesive bonding processes). Therefore, we investigate how Augmented Reality (AR) can improve workers’ performance in time and spatial dependent process steps. In a user study, we compare three conditions: instructions presented on (a) paper, (b) a camera-based see-through tablet, and (c) a head-mounted AR device. For instructions we used selected work steps from a standardized adhesive bonding process as a representative for common time-critical assembly tasks. We found that instructions in AR can improve the performance and understanding of time and spatial factors. The tablet instruction condition showed the best subjective results among the participants, which can increase motivation, particularly among less-experienced workers.

  • Faltaous, Sarah; Neuwirth, Joshua; Gruenefeld, Uwe; Schneegass, Stefan: SaVR: Increasing Safety in Virtual Reality Environments via Electrical Muscle Stimulation. In: 19th International Conference on Mobile and Ubiquitous Multimedia (MUM). Association for Computing Machinery, Essen, Germany 2020, S. 254-258. doi:10.1145/3428361.3428389BIB DownloadDetails

    One of the main benefits of interactive Virtual Reality (VR) applications is that they provide a high sense of immersion. As a result, users lose their sense of real-world space which makes them vulnerable to collisions with real-world objects. In this work, we propose a novel approach to prevent such collisions using Electrical Muscle Stimulation (EMS). EMS actively prevents the movement that would result in a collision by actuating the antagonist muscle. We report on a user study comparing our approach to the commonly used feedback modalities: audio, visual, and vibro-tactile. Our results show that EMS is a promising modality for restraining user movement and, at the same time, rated best in terms of user experience.

  • Gruenefeld, Uwe; Brueck, Yvonne; Boll, Susanne: Behind the Scenes: Comparing X-Ray Visualization Techniques in Head-Mounted Optical See-through Augmented Reality. In: 19th International Conference on Mobile and Ubiquitous Multimedia (MUM). Association for Computing Machinery, Essen, Germany 2020, S. 179-185. doi:10.1145/3428361.3428402BIB DownloadDetails

    Locating objects in the environment can be a difficult task, especially when the objects are occluded. With Augmented Reality, we can alternate our perceived reality by augmenting it with visual cues or removing visual elements of reality, helping users to locate occluded objects. However, to our knowledge, it has not yet been evaluated which visualization technique works best for estimating the distance and size of occluded objects in optical see-through head-mounted Augmented Reality. To address this, we compare four different visualization techniques derived from previous work in a laboratory user study. Our results show that techniques utilizing additional aid (textual or with a grid) help users to estimate the distance to occluded objects more accurately. In contrast, a realistic rendering of the scene, such as a cutout in the wall, resulted in higher distance estimation errors.

  • Auda, Jonas; Gruenefeld, Uwe; Mayer, Sven: It Takes Two To Tango: Conflicts Between Users on the Reality-Virtuality Continuum and Their Bystanders. In: Proceedings of the 14th ACM Interactive Surfaces and Spaces (ISS). Association for Computing Machinery, Lisbon, Portugal 2020. BIB DownloadDetails

    Over the last years, Augmented and Virtual Reality technology became more immersive. However, when users immerse themselves in these digital realities, they detach from their real-world environments. This detachment creates conflicts that are problematic in public spaces such as planes but also private settings. Consequently, on the one hand, the detaching from the world creates an immerse experience for the user, and on the other hand, this creates a social conflict with bystanders. With this work, we highlight and categorize social conflicts caused by using immersive digital realities. We first present different social settings in which social conflicts arise and then provide an overview of investigated scenarios. Finally, we present research opportunities that help to address social conflicts between immersed users and bystanders.

  • Schneegaß, Stefan; Auda, Jonas; Heger, Roman; Grünefeld, Uwe; Kosch, Thomas: EasyEG: A 3D-printable Brain-Computer Interface. In: Proceedings of the 33rd ACM Symposium on User Interface Software and Technology (UIST). Minnesota, USA 2020. doi:10.1145/3379350.3416189BIB DownloadDetails

    Brain-Computer Interfaces (BCIs) are progressively adopted by the consumer market, making them available for a variety of use-cases. However, off-the-shelf BCIs are limited in their adjustments towards individual head shapes, evaluation of scalp-electrode contact, and extension through additional sensors. This work presents EasyEG, a BCI headset that is adaptable to individual head shapes and offers adjustable electrode-scalp contact to improve measuring quality. EasyEG consists of 3D-printed and low-cost components that can be extended by additional sensing hardware, hence expanding the application domain of current BCIs. We conclude with use-cases that demonstrate the potentials of our EasyEG headset.

  • Gruenefeld, Uwe; Prädel, Lars; Illing, Jannike; Stratmann, Tim; Drolshagen, Sandra; Pfingsthorn, Max: Mind the ARm: Realtime Visualization of Robot Motion Intent in Head-Mounted Augmented Reality. In: Proceedings of the Conference on Mensch Und Computer (MuC). Association for Computing Machinery, 2020, S. 259-266. doi:10.1145/3404983.3405509BIB DownloadDetails

    Established safety sensor technology shuts down industrial robots when a collision is detected, causing preventable loss of productivity. To minimize downtime, we implemented three Augmented Reality (AR) visualizations (Path, Preview, and Volume) which allow users to understand robot motion intent and give way to the robot. We compare the different visualizations in a user study in which a small cognitive task is performed in a shared workspace. We found that Preview and Path required significantly longer head rotations to perceive robot motion intent. Volume, however, required the shortest head rotation and was perceived as most safe, enabling closer proximity of the robot arm before one left the shared workspace without causing shutdowns.

  • Saad, Alia; Wittig, Nick; Grünefeld, Uwe; Schneegass, Stefan: A Systematic Analysis of External Factors Affecting Gait Identification. . BIB DownloadDetails