Veröffentlichungen

@inproceedings{10445600,

title = {Enhancing Human-Robot Interaction Research by Using a Virtual Reality Lab Approach},

author = {Alexander Arntz and André Helgert and Carolin Straßmann and Sabrina C. Eimler},

doi = {10.1109/AIxVR59861.2024.00058},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)},

pages = {340-344},

abstract = {Human-robot interaction (HRI) research often faces limitations in real-world environments due to uncontrollable external factors. This applies in particular to field study setups in public spaces, as these can limit the validity of the study results, e.g. due to unpredictable and unsystematic changes in the environment, noise, people passing, etc. Especially for interdisciplinary studies involving psychological perspectives, virtual reality (VR) has emerged as a promising solution, offering realistic, controlled, and reproducible environments. Also, recent technological advancements enable detailed observation of human behavior and physiological responses via eye tracking, physiological assessments, and motion capture. To effectively add value by using VR as a tool, immersion, and presence in the virtual environment are essential preconditions. Besides, the manipulability of the VR environment during runtime is a bonus in exploring human behavior in interaction with robot-enriched spaces. As a methodological innovation in HRI studies, this paper presents a VR lab as a research tool that provides a virtual model of the robot Pepper along with interfaces for easy navigation and adaptive robot behavior. Moreover, the presented Wizard of Oz dashboard allows to flexibly react to the scenery by allowing the manipulation of several robot parameters during runtime. With the help of the VR lab, a framework for a variety of interdisciplinary research purposes in human-robot interaction (not only) in public spaces is provided.},

keywords = {Technological innovation;Solid modeling;Runtime;Human-robot interaction;Virtual environments;Physiology;Robots;Virtual Reality;Human-Robot Interaction;Empirical Studies;Research Platform;Study Tool;Wizard of Oz},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10445553,

title = {Virtual Reality for Tinnitus Education: Inspiring Awareness and Proactive Behavioral Changes},

author = {Dan Heilmann and André Helgert and Sabrina C. Eimler},

doi = {10.1109/AIxVR59861.2024.00049},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)},

pages = {294-300},

abstract = {Tinnitus is a prevalent symptom in otorhinolaryngology affecting a substantial portion of the population. Factors contributing to tinnitus include acoustic stress, sensory overload, and neurological and psychological disturbances. Although associated comorbidities can be treated, tinnitus lacks a definitive cure. Consequently, preventive measures and awareness about its consequences are crucial. Virtual Reality (VR) emerges as a potential tool for assistance as it offers (often appealing) immersive simulations, combining visual and auditory perceptual inputs supporting a feeling of being in a real physical environment. As it could help to effectively recreate the experience of tinnitus in everyday situations, VR may facilitate a deep sense of empathy and comprehension. As a first step in designing the application, a pre-study collected scenarios among people (N = 32) with tinnitus symptoms. These were subsequently implemented in the VR application and evaluated by students (N = 22) without tinnitus symptoms. The application aims to recreate distressing scenarios, to elicit empathy and educate unaffected individuals.},

keywords = {Visualization;Solid modeling;Sociology;Psychology;Virtual reality;Human factors;Statistics;virtual reality;tinnitus;sensitization;immersion;simulation;health promotion;awareness},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3610978.3640741,

title = {Unlocking Potentials of Virtual Reality as a Research Tool in Human-Robot Interaction: A Wizard-of-Oz Approach},

author = {André Helgert and Carolin Straßmann and Sabrina C. Eimler},

url = {https://doi.org/10.1145/3610978.3640741},

doi = {10.1145/3610978.3640741},

isbn = {9798400703232},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction},

pages = {535–539},

publisher = {Association for Computing Machinery},

address = {Boulder, CO, USA},

series = {HRI '24},

abstract = {Wizard-of-Oz (WoZ) systems represent a widespread method in HRI research. While they are cost-effective, flexible and are often preferred over developing autonomous dialogs in experimental settings, they are typically tailored to specific use cases. In addition, WoZ systems are mainly used in lab studies that deviate from real world scenarios. Here, virtual reality (VR) can be used to immerse the user in a real world interaction scenario with robots. This article highlights the necessity for a modularized and customizable WoZ system, using the benefits of VR. The proposed system integrates well-established features like speech and gesture control, while expanding functionality to encompass a data dashboard and dynamic robot navigation using VR technology. The discussion emphasizes the importance of developing technical systems, like the WoZ system, in a modularized and customizable way, particularly for non-technical researchers. Overcoming usability hurdles is crucial to establishing this tool's role in the HRI research field.},

keywords = {accessibility, social robots, virtual reality, Wizard-of-Oz},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-60412-6_4,

title = {Enabling Safe Empirical Studies for Human-Robot Collaboration: Implementation of a Sensor Array Driven Control Interface},

author = {Alexander Arntz},

editor = {Masaaki Kurosu and Ayako Hashizume},

isbn = {978-3-031-60412-6},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {Human-Computer Interaction},

pages = {42–57},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {In response to the growing relevance of collaborative robots, the need for empirical user studies in the domain of Human-Robot Collaboration become increasingly important. While collaborative robots incorporate internal safety features, their usage for user studies remains associated with inherent safety risks. This project addresses these challenges by introducing a toolbox for a robot arm to conduct Wizard-of-Oz studies by using advanced controls complemented by a sophisticated security system leveraging microcontrollers and human presence detection sensors. This approach unifies both control systems within a single application, seamlessly monitoring and synchronizing their respective inputs. The gamepad control scheme offers Wizard-of-Oz study supervisors an intuitive means of interacting with the robot, enabling precise and responsive control while maintaining safety. Meanwhile, the security system, built on microcontroller technology and human presence detection sensors, acts as a vigilant guardian, continuously assessing the robot's surroundings for potential risks. This integrated application not only empowers users with effective control over the xArm 7 but also provides real-time feedback on the security status, enhancing the overall safety and usability of collaborative robots in various industrial settings. By bridging the gap between human operators and robots, this project contributes to the evolution of safer and more user-friendly human-robot collaboration.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10445597,

title = {Teamwork Makes the Dream Work: A Virtual Reality-based Human-Robot Collaboration Sandbox Simulating Multiple Teams},

author = {Alexander Arntz and Agostino Di Dia and Tim Riebner and Carolin Straßmann and Sabrina C. Eimler},

doi = {10.1109/AIxVR59861.2024.00057},

issn = {2771-7453},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR)},

pages = {335-339},

abstract = {We present a virtual reality-based Human-Robot Collaboration sandbox that allows the representation of multiple teams composed of humans and robots. Within the sandbox, virtual robots and humans can collaborate with their respective partners and interact with other teams to coordinate the required procedures while accomplishing a shared task. For this purpose, the virtual reality sandbox is equipped with a variety of interaction mechanics that enable a range of different shared tasks. The network integration allows for multiple users within the virtual environment. The VR application contains a library of different industrial robots that can act autonomously controlled by machine learning agents and interact with the user through verbal commands. The sandbox is specifically designed to serve as a research tool to explore new concepts and validate existing approaches in the domain of Human-Robot Collaboration involving autonomous robots in a series of upcoming studies.},

keywords = {Robot kinematics;Virtual assistants;Virtual environments;Industrial robots;Libraries;Teamwork;Task analysis;Human-Robot Collaboration;Virtual Reality;Machine Learning;Artificial Intelligence},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sziburisVariabilityStudyHuman2023,

title = {Variability Study of Human Hand Motion during 3D Center-out Tasks Captured for the Diagnosis of Movement Disorders},

author = {Tim Sziburis and Susanne Blex and Ioannis Iossifidis},

year  = {2023},

date = {2023-09-15},

urldate = {2023-09-15},

booktitle = {BC23 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

abstract = {Variability analysis bears the potential to differentiate between healthy and pathological human movements [1]. Our study is conducted in the context of developing a portable glove for the diagnosis of movement disorders. This proposal has methodical as well as technical requirements. Generally, the identification of movement disorders via an analysis of motion data needs to be confirmed within the given setup. Typically, rhythmic movements like gait or posture control are examined for their variability, but here, the characteristic pathological traits of arm movement like tremors are under observation. In addition, the usability of a portable sensor instead of a stationary tracking system has to be validated. In this part of the project, human motion data are recorded redundantly by both an optical tracking system and an IMU. In our setup, a small cylinder is transported in three-dimensional space from a unified start position to one of nine target positions, which are equidistantly aligned on a semicircle. 10 trials are performed per target and hand, resulting in 180 trials per participant in total. 31 participants (11 female and 20 male) without known movement disorders, aged between 21 and 78 years, took part in the study. In addition, the 10-item EHI is used. The purpose of the analysis is to compare different variability measures to uncover differences between trials (intra-subject variability) and participants (inter-subject variability), especially in terms of age and handedness effects. Particularly, a novel variability measure is introduced which makes use of the characteristic planarity of the examined hand paths [2]. For this, the angle of the plane which best fits the travel phase of the trajectory is determined. In addition to neurological motivation, the advantage of this measure is that it allows the comparison of trials of different time spans and to different target directions without depending on trajectory warping. In the future, measurements of the same experimental setup with patients experiencing movement disorders are planned. For the subsequent pathological analysis, this study provides a basis in terms of methodological considerations and ground truth data of healthy participants. In parallel, the captured motion data are modelled utilizing dynamical systems (extended attractor dynamics approach). For this approach, the recorded and modelled data can be compared by the variability measures examined in this study.},

keywords = {movement model},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{xavierfidencioExploringErrorrelatedPotentials2023,

title = {Exploring Error-related Potentials in Adaptive Brain-Machine Interfaces: Challenges and Investigation of Occurrence and Detection Ratios},

author = {Aline Xavier Fidencio and Christian Klaes and Ioannis Iossifidis},

year  = {2023},

date = {2023-09-15},

urldate = {2023-09-15},

booktitle = {BC23 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

abstract = {Non-invasive techniques like EEG can record error-related potentials (ErrPs), neural signals associated with error processing and awareness. ErrPs are generated in response to self-made and external errors, including those produced by the BMI. Since ErrPs are implicitly elicited and don’t add extra workload for the subject, they serve as a natural and intrinsic feedback source for developing adaptive BMIs. In our study, we assess the occurrence of interaction ErrPs in an adaptive BMI that combines ErrPs and reinforcement learning. We intentionally provoke ErrPs when the BMI misinterprets the user’s intention and performs an incorrect action. Subjects participated in a game controlled by a keyboard and/or motor imagery (imagining hand movements), and EEG data were recorded using an eight-electrode gel-based EEG system. Results reveal that obtaining a distinct ErrPs signal for each subject is more challenging than anticipated. Current practices report the ErrP in terms of over all subjects and trials difference grand average (error minus correct). This approach has, however, the limitation of masking the inter-trial and subject variability, which are relevant for the online single-trial detection of such signals. Moreover, the reported ErrPs waveshape exhibit differences in terms of components observed, as well as their respective latencies, even when very similar tasks are used. Consequently, we conducted additional individualized data analysis to gain deeper insights into the single-trial nature of the ErrPs. As a result, we determined the need for a better understanding and further investigation of how effectively the ErrPs waveforms generalize across subjects, tasks, experimental protocols, and feedback modalities. Given the challenges in obtaining a clear signal for all subjects and the limitations found in existing literature (Xavier Fidêncio et al., 2022), we hypothesize whether an error signal measurable at the scalp level is consistently generated when subjects encounter erroneous conditions. To address this question, we will assess the occurrence-to-detection ratio of ErrPs using invasive and non-invasive recording techniques, examining how uncertainties regarding error generation in the brain impact the learning pipeline.},

keywords = {BCI, EEG, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{grunInvestigationInterplayModelBased2023,

title = {Investigation of the Interplay of Model-Based and Model-Free Learning Using Reinforcement Learning},

author = {Felix Grün and Ioannis Iossifidis},

year  = {2023},

date = {2023-09-15},

urldate = {2023-09-15},

booktitle = {BC23 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

abstract = {The reward prediction error hypothesis of dopamine in the brain states that activity of dopaminergic neurons in certain brain regions correlates with the reward prediction error that corresponds to the temporal difference error, often used as a learning signal in model free reinforcement learning (RL). This suggests that some form of reinforcement learning is used in animal and human brains when learning a task. On the other hand, it is clear that humans are capable of building an internal model of a task, or environment, and using it for planning, especially in sequential tasks. In RL, these two learning approaches, model-driven and reward-driven, are known as model based and model-free RL approaches. Both systems were previously thought to exist in parallel, with some higher process choosing which to use. A decade ago, research suggested both could be used concurrently, with some subject-specific weight assigned to each [1]. Still, the prevalent belief appeared to be that model-free learning is the default mechanism used, replaced or assisted by model-based planning only when the task demands it, i.e. higher rewards justify the additional cognitive effort. Recently, Feher da Silva et al. [2] questioned this belief, presenting data and analyses that indicate model-based learning may be used on its own and can even be computationally more efficient. We take a RL perspective, consider different ways to combine model-based and model-free approaches for modeling and for performance, and discuss how to further study this interplay in human behavioral experiments.},

keywords = {Machine Learning, Reinforcement learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schmidtLinkMuscleActivity2023,

title = {The Link between Muscle Activity and Upper Limb Kinematics},

author = {Marie Dominique Schmidt and Ioannis Iossifidis},

year  = {2023},

date = {2023-09-15},

urldate = {2023-09-15},

booktitle = {BC23 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

abstract = {The upper limbs are crucial in performing daily tasks that require strength, a wide range of motion, and precision. To achieve coordinated motion, planning and timing are critical. Sensory information about the target and the current body state is essential, as well as integrating past experiences, represented by pre-learned inverse dynamics that generate associated muscle activity. We propose a generative model that predicts upper limb muscle activity from a variety of simple and complex everyday motions by means of a recurrent neural network. The model shows promising results, with a good fit for different subjects and abstracts well for new motions. We handle the high inter-subject variation in muscle activity using a transfer learning approach, resulting in a good fit for new subjects. Our approach has implications for fundamental movement control understanding and the rehabilitation of neuromuscular diseases using myoelectric prostheses and functional electrical stimulation. Our model can efficiently predict both muscle activity and motion trajectory, which can assist in developing more effective rehabilitation techniques.},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Börsting2023,

title = {Tell me why - Combating racism on social media with knowledge},

author = {Johanna Börsting and Veronica Schwarze and Sabrina C. Eimler},

editor = {André Melzer and Gary Lee Wagener},

url = {https://doi.org/10.26298/1981-5555},

year  = {2023},

date = {2023-09-06},

booktitle = {Proceedings of the 13th Conference of the Media Psychology Division (DGPs)},

publisher = {Melusina Press},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Erle2023,

title = {Algorithmic Bias and Digital Divide – An Examination of Discrimination Experiences in Human-System Interactions (Poster)},

author = {Lukas Erle and Lara Timm and Carolin Straßmann and Sabrina C. Eimler},

editor = {André Melzer and Gary Lee Wagener},

url = {https://doi.org/10.26298/1981-5555},

year  = {2023},

date = {2023-09-06},

booktitle = {Proceedings of the 13th Conference of the Media Psychology Division (DGPs)},

publisher = {Melusina Press},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {Imagine it was you - Empathy as the key for reducing cyberbullying on social media},

author = {Sabrina C. Eimler and Johanna Börsting and Veronica Schwarze},

editor = {André Melzer and Gary Lee Wagener},

url = {https://doi.org/10.26298/1981-5555},

year  = {2023},

date = {2023-09-06},

booktitle = {Proceedings of the 13th Conference of the Media Psychology Division (DGPs)},

publisher = {Melusina Press},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Schwarze2023,

title = {Picturing diversity: Exploring children’s perception of intergroup differences },

author = {Veronica Schwarze and Sabrina C. Eimler and Nicole C. Krämer},

editor = {André Melzer and Gary Lee Wagener},

url = {https://doi.org/10.26298/1981-5555},

year  = {2023},

date = {2023-09-06},

booktitle = {Proceedings of the 13th Conference of the Media Psychology Division (DGPs)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Schweizer2023,

title = {Keep calm - The role of resilience in the interplay between neuroticism and phubbing },

author = {Anne-Marie Schweizer and Johanna Börsting},

editor = {André Melzer and Gary Lee Wagener},

url = {https://doi.org/10.26298/1981-5555},

year  = {2023},

date = {2023-09-06},

urldate = {2023-09-06},

booktitle = {Proceedings of the 13th Conference of the Media Psychology Division (DGPs)},

publisher = {Melusina Press},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10309310,

title = {Exploring the Use of Colored Ambient Lights to Convey Emotional Cues With Conversational Agents: An Experimental Study},

author = {Carolin Straßmann and André Helgert and Valentin Breil and Lina Settelmayer and Inga Diehl},

doi = {10.1109/RO-MAN57019.2023.10309310},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)},

pages = {99-105},

abstract = {Conversational agents (CAs) lack of possibilities to enrich the interaction with emotional cues, although this makes the conversation more human-like and enhances user engagement. Thus, the potential of CAs is not fully exploit and possibilities to convey emotional cues are needed. In this work, CAs use colored ambient lights to display moral emotions during the interaction. To evaluate this approach, a between-subject lab experiment (N=64) was conducted. Participants played a cooperation game with Amazon’s Alexa. Depending on the experimental condition participants received different light expressions: no light, neutral light, or morally emotional light (yellow = joy, blue = sorrow, red = anger matching the game decisions). The effect of the light expressions on the perception of the CA, users’ empathy and cooperation behavior was tested. Against our assumptions, the results indicated no positive effect of the emotional light cues. Limitations, next steps, and implications are discussed.},

keywords = {Ethics;Emotion recognition;Virtual assistants;Games;Behavioral sciences;Robots},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-29800-4_52,

title = {Psychological Outcomes and Effectiveness of a Collaborative Video-Based Learning Tool for Synchronous Discussions},

author = {Carolin Straßmann and André Helgert and Andreas Lingnau},

editor = {Giovanni Fulantelli and Daniel Burgos and Gabriella Casalino and Marta Cimitile and Giosuè Lo Bosco and Davide Taibi},

isbn = {978-3-031-29800-4},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {Higher Education Learning Methodologies and Technologies Online},

pages = {691–705},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {In the context of digitization and the COVID-19 pandemic, online teaching comes more and more into focus of higher education. Various online learning methodologies such as using videos as a teaching method are promising, but can also create problems in the area of social relations or learning habits. The concept of collaborative learning, especially in an online environment, could counteract these problems. This paper presents a collaborative online learning tool that allows students to get together in learning groups to watch educational videos together. Various functions, such as a chat, help students to communicate with each other. A psychological evaluation was conducted to investigate the effects on students. The evaluation demonstrated positive effects of the tool, since it enhances important psychological processes (like flow and cognitive load) within the learning process. Moreover, its usability was rated as good and participants showed a high usage intention for the tool. Nevertheless, further investigations in long-term learning courses are needed to finally confirm the tool's effectiveness.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-29800-4_27,

title = {Empirically Investigating Virtual Learning Companions to Enhance Social Media Literacy},

author = {Emily Theophilou and Veronica Schwarze and Johanna Börsting and Roberto Sánchez-Reina and Lidia Scifo and Francesco Lomonaco and Farbod Aprin and Dimitri Ognibene and Davide Taibi and Davinia Hernández-Leo and Sabrina C. Eimler},

editor = {Giovanni Fulantelli and Daniel Burgos and Gabriella Casalino and Marta Cimitile and Giosuè Lo Bosco and Davide Taibi},

isbn = {978-3-031-29800-4},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {Higher Education Learning Methodologies and Technologies Online},

pages = {345–360},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {Social media platforms provide opportunities for users across the world to connect and communicate between them and engage into acts of social support and entertainment. Yet it can also bring negative consequences as it has been associated with poor mental health and life dissatisfaction. This underlines the importance of delivering social media literacy (SML) interventions that raise awareness of the dangers and threats that are hidden within. To this date, SML initiatives have shown their benefits towards the acquisition of SML skills through the forms of school interventions and mini-games. However, studies on promoting SML through social media platforms need to be also encouraged and innovative approaches to provide interactive scenarios with hands-on experiences need to be formulated. Hence, the project COURAGE introduces a new approach towards SML by proposing the integration of educational opportunities within a controlled social media platform. To provide students the opportunity to learn whilst they naturally explore social media we propose the integration of virtual learning companions. In this paper we report seven empirical approaches towards SML skills acquisition powered by virtual learning companions. The paper concludes with a discussion towards the benefits and limitations of using this type of SML interventions.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-29800-4_25,

title = {The Role of Educational Interventions in Facing Social Media Threats: Overarching Principles of the COURAGE Project},

author = {Davide Taibi and Johanna Börsting and Ulrich Hoppe and Dimitri Ognibene and Davinia Hernández-Leo and Sabrina C. Eimler and Udo Kruschwitz},

editor = {Giovanni Fulantelli and Daniel Burgos and Gabriella Casalino and Marta Cimitile and Giosuè Lo Bosco and Davide Taibi},

isbn = {978-3-031-29800-4},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {Higher Education Learning Methodologies and Technologies Online},

pages = {315–329},

publisher = {Springer Nature Switzerland},

address = {Cham},

abstract = {Social media are offering new opportunities for communication and interaction way beyond what was possible only a few years ago. However, social media are also virtual spaces where young people are exposed to a variety of threats. Digital addiction, discrimination, hate speech, misinformation, polarization as well as manipulative influences of algorithms, body stereotyping, and cyberbullying are examples of challenges that find fertile ground on social media. Educators and students are not adequately prepared to face these challenges. To this aim, the COURAGE project, presented in this paper, introduces new tools and learning methodologies that can be adopted within higher education learning paths to train educators to deal with social media threats. The overarching principles of the COURAGE project leverage the most recent advances in the fields of artificial intelligence and in the educational domain paired with social and media psychological insights to support the development of the COURAGE ecosystem. The results of the experiments currently implemented with teachers and students of secondary schools as well as the impact of the COURAGE project on societal changes and ethical questions are presented and discussed.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-21229-1_13,

title = {Prototyping a Smart Contract Application for Fair Reward Distribution in Software Development Projects},

author = {Agostino Di Dia and Tim Riebner and Alexander Arntz and Marc Jansen},

editor = {Javier Prieto and Francisco Luis Benítez Martínez and Stefano Ferretti and David Arroyo Guardeño and Pedro Tomás Nevado-Batalla},

isbn = {978-3-031-21229-1},

year  = {2023},

date = {2023-01-01},

booktitle = {Blockchain and Applications, 4th International Congress},

pages = {131--141},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {The following work describes the development of a project management platform based on the waves blockchain technology. The aim is to use the platform to optimally reward both fairness and the achievement of quality standards in software development. Due to the outsourcing of software projects and the associated processes, situations arise in which different project participants work on the same tasks, while paid differently and in most cases independent of the delivered software quality. This is based on the respective contract conditions an individual software developer has negotiated, without factoring in the actual quality of the code the developer provided. The proposal of this work is a prototypical software application that takes the requirements of a project and measures the corresponding contributions of the developers based on their software quality. Project sponsors can also pay out the enrolled project partners via the platform.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{grunExploringDistributionParameterizations2022,

title = {Exploring Distribution Parameterizations for Distributional Continuous Control},

author = {Felix Grün and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2022.112},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

booktitle = {BC22 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {Machine Learning, Reinforcement learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lehmlerModelingSubjectSpecfic2022,

title = {Modeling Subject Specfic Surface EMG Features by Means of Deep Learning},

author = {Stephan Johann Lehmler and Muhammad Saif-ur-Rehman and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2022.309},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

booktitle = {BC22 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schmidtLinkingMuscleActivity2022,

title = {Linking Muscle Activity and Motion Trajectory},

author = {Marie Dominique Schmidt and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2022.191},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

booktitle = {BC22 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sziburisDataset3DHand2022,

title = {A Dataset of 3D Hand Transport Trajectories Determined by Inertial Measurements from a Single Sensor},

author = {Tim Sziburis and Susanne Blex and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2022.186},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

booktitle = {BC22 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{xavierfidencioClosedloopAdaptationBrainmachine2022,

title = {Closed-Loop Adaptation of Brain-Machine Interfaces Using Error-Related Potentials and Reinforcement Learning},

author = {Aline Xavier Fidencio and Christian Klaes and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2022.136},

year  = {2022},

date = {2022-09-15},

urldate = {2022-09-15},

booktitle = {BC22 : Computational Neuroscience & Neurotechnology Bernstein Conference 2022},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{doliwaBiologicallyInspiredModel2022,

title = {Biologically Inspired Model for Timed Motion in Robotic Systems},

author = {Sebastian Doliwa and Muhammad Ayaz Hussain and Tim Sziburis and Ioannis Iossifidis},

year  = {2022},

date = {2022-08-12},

urldate = {2022-08-12},

booktitle = {9th IEEE RAS/EMBS International Conference on Biomedical Robotics & Biomechatronics},

publisher = {IEEE},

address = {Seoul, South Korea},

keywords = {Autonomous robotics, Dynamical systems},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{9853790,

title = {A Framework for Analyzing Interactions in a Video-based Collaborative Learning Environment},

author = {André Helgert and Anil Canbulat and Andreas Lingnau and Carolin Straßmann},

doi = {10.1109/ICALT55010.2022.00045},

issn = {2161-377X},

year  = {2022},

date = {2022-07-01},

urldate = {2022-07-01},

booktitle = {2022 International Conference on Advanced Learning Technologies (ICALT)},

pages = {125-127},

abstract = {Studying in social isolation is a reality for many students that was further reinforced after the start of the COVID-19 pandemic. Research shows that isolation can lead to decreased learning efficiency and is intensified by the increased asynchronous online teaching during the pandemic. This change is not only challenging for students, but also for teachers, as students do not have a direct communication and feedback channel when learning content is presented in form of pre-recorded videos in a learning management system. In this paper, we present VGather2Learn Analytics, which is an extension to the already existing collaborative learning system VGather2Learn, which makes it possible for teachers to analyse the learning behavior of students in asynchronous video-teaching. The information presented in a dashboard will allow teachers to better understand how students interact while watching learning videos collaboratively and can improve online-teaching.},

keywords = {COVID-19;Learning management systems;Pandemics;Distance learning;Collaboration;Collaborative work;Behavioral sciences;Learning Analytics;Computer-supported Collaborative Learning;Social Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{doliwaDevelopmentScalableAnalogaccepted,

title = {Development of a Scalable Analog Front-End for Brain-Computer Interfaces},

author = {Sebastian Doliwa and Andreas Erbeslöh and Karsten Seidl and Ioannis Iossifidis},

year  = {2022},

date = {2022-06-15},

urldate = {2022-06-15},

booktitle = {17th International Conference on PhD Research in Microelectronics and Electronics},

publisher = {IEEE Prime 2022},

address = {Sardinia, Italy},

keywords = {BCI, Implantable BCI},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10024471,

title = {A Qualitative Analysis of Interaction Techniques in a Virtual Reality Instruction Environment: Experiences From a Case Study},

author = {André Helgert and Anna Groeneveld and Sabrina C. Eimler},

doi = {10.1109/AIVR56993.2022.00034},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {2022 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)},

pages = {171-175},

abstract = {As they can immerse people into virtual worlds free from external distraction, virtual reality (VR) applications are an important factor in research today and can be useful in various scenarios such as intervention training, simulations and in learning environments. However, many people are not used to interacting and navigating in VR and may not have much prior technical experience, which can become a distracting factor to the content and can influence success negatively. Thus, benefits of VR-environments cannot be fully exploited. Aiming to counteract the problem that people cannot take advantage of the benefits of VR-applications, an instruction room for training representative interaction patterns, i.e. interaction and locomotion mechanics, was designed. Students (N = 12) were videotaped going through six stations of the instruction room with different interaction tasks. They were prompted to think aloud to capture their thoughts (e.g., intuitiveness, usability and expansion ideas) while interacting, and interviewed afterwards for an overall assessment. A qualitative content analysis helped to identify patterns. Interactions like localization field triggers for instructions and answering a quiz were regarded as highly intuitive, giving feedback with a drum keyboard was reported as most entertaining.},

keywords = {Training;Location awareness;Solid modeling;Navigation;Keyboards;Virtual reality;Usability;virtual reality;interaction mechanics;interaction patterns;think aloud;virtual environment;virtual interactions;accessibility},

pubstate = {published},

tppubtype = {inproceedings}

}