Veröffentlichungen

@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}

}

@inproceedings{fidencioErrorrelatedPotentialsDetection2022,

title = {Error-Related Potentials Detection with Dry- and Wet-Electrode EEG},

author = {Aline Xavier Fidencio and Tobias Glasmachers and Ioannis Iossifidis},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {FENS, Forum 2022},

publisher = {FENS, Federation of European Neuroscience Societies},

abstract = {Electroencephalography (EEG) is a non-invasive technique for measuring brain electrical activity from electrodes placed on the scalp surface. Improvements in this technology are particularly relevant because they also boost brain-machine interfaces (BMI) development. Commonly, gel-based electrodes are used since they guarantee a high-quality signal. Alternatively, dry electrodes have been introduced, more suitable for daily use. In this work, we compare conventional dry and wet electrode systems specifically for the detection of error-related potentials (ErrPs). ErrPs are elicited as a reaction to both self-made and external errors. There has been increased interest in the integration of these signals into BMIs to improve their performance since they provide a convenient source of feedback to the system with no extra workload for the subject. These signals can be used, e.g., to correct errors or even for system adaptation. ErrP-based BMIs in the literature have consistently used wet electrodes. Therefore, even though both electrodes types have been compared for other event-related potentials (e.g., P300), it is relevant to know whether the signal quality for the detection of ErrPs is comparable among them. In this work, we implement a simple game to elicit ErrPs and compare the quality of the measured signals. We tested the feasibility of the experimental protocol to elicit ErrP and the measured ErrP displayed a similar waveshape in terms of observed peaks. However, differences exist in both latencies as well as in their amplitude. These variations and other relevant characteristics have to be further verified with more subjects},

keywords = {BCI, EEG, error-related potentials, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schmidtMotionIntentionPrediction2022a,

title = {Motion Intention Prediction},

author = {Marie Dominique Schmidt and Tobias Glasmachers and Ioannis Iossifidis},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {FENS, Forum 2022},

publisher = {FENS, Federation of European Neuroscience Societies},

abstract = {Motion intention prediction is the key to robot-assisted rehabilitation systems. These can rely on various biological signals. One commonly used signal is the muscle activity measured by an electromyogram that occurs between 50-100 milliseconds before the actual movement, allowing a real-world application to assist in time. We show that upper limb motion can be estimated from the corresponding muscle activity. To this end, eight-arm muscles are mapped to the joint angle, velocity, and acceleration of the shoulder, elbow, and wrist. For this purpose, we specifically develop an artificial neural network that estimates complex motions involving multiple upper limb joints. The network model is evaluated concerning its ability to generalize across subjects as well as for new motions. This is achieved through training on multiple subjects and additional transfer learning methods so that the prediction for new subjects is significantly improved. In particular, this is beneficial for a robust real-world application. Furthermore, we investigate the importance of the different parameters such as angle, velocity, and acceleration for simple and complex motions. Predictions for simple motions along with the main components of complex motions achieve excellent accuracy while joints that do not play a dominant role during the motion have comparatively lower accuracy.},

keywords = {BCI, Machine Learning, movement model, muscle signal generator, recurrent neural network},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{mci/Helgert2022,

title = {DiSensity: Ein hochschulweites Virtual Reality Sensibilisierungsprogramm},

author = {André Helgert and Laura Zielinska and Anna Groeneveld and Chiara Kloos and Alexander Arntz and Carolin Straßmann and Sabrina C. Eimler},

editor = {Heinrich Söbke and Raphael Zender},

doi = {10.18420/avril2022_03},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {Wettbewerbsband AVRiL 2022},

pages = {17-22},

publisher = {Gesellschaft für Informatik e.V.},

address = {Bonn},

abstract = {Diversitätsbezogene Herausforderungen begegnen den meisten Studierenden, Lehrenden und Mitarbeitenden immer wieder im Hochschulalltag. Manchmal wird uns dies nicht bewusst, da wir nicht ausreichend für das Thema sensibilisiert sind und uns Situationen aus unserer eigenen Perspektive unproblematisch erscheinen oder wir ihnen aus dem Weg gehen, wenn sie uns unangenehm sind. Aus diesen Erfahrungen kann eine Schieflage in der Kommunikation oder der Wahrnehmung der anderen Person entstehen, die Probleme, Konflikte oder ein Gefühl sozialer Isolation erzeugt. In diesem Beitrag wird eine immersive Virtual-Reality-Galerie vorgestellt, welche von Akteur:innen aus den Fach- und Servicebereichen und Studierenden entwickelt wird. Das Ziel ist es, die Sensibilität für Vielfalt und deren Bedeutung im Lehr- und Lerngeschehen hochschulweit und bei allen Akteursgruppen zu steigern. Mit dem Einsatz von multimedialen Inhalten und verschiedenen Interaktionsmechaniken in der virtuellen Welt, kann DiSensity als effiziente, kostengünstige und flexible Alternative zu bisherigen Diversitäts Trainings dienen.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-05014-5_30,

title = {Effects of the Surroundings in Human-Robot Interaction: Stereotypical Perception of Robots and Its Anthropomorphism},

author = {Carolin Straßmann and Sabrina C. Eimler and Linda Kololli and Alexander Arntz and Katharina Sand and Annika Rietz},

editor = {Gavriel Salvendy and June Wei},

isbn = {978-3-031-05014-5},

year  = {2022},

date = {2022-01-01},

booktitle = {Design, Operation and Evaluation of Mobile Communications},

pages = {363--377},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {Stereotypes and scripts guide human perception and expectations in everyday life. Research has found that a robot's appearance influences the perceived fit in different application domains (e.g. industrial or social) and that the role a robot is presented in predicts its perceived personality. However, it is unclear how the surroundings as such can elicit a halo effect leading to stereotypical perceptions. This paper presents the results of an experimental study in which 206 participants saw 8 cartoon pictures of the robot Pepper in different application domains in a within-subjects online study. Results indicate that the environment a robot is placed in has an effect on the users' evaluation of the robot's warmth, competence, status in society, competition, anthropomorphism, and morality. As the first impression has an effect on users' expectations and evaluation of the robot and the interaction with it, the effect of the application scenarios has to be considered carefully.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-05431-0_1,

title = {Augmented Reality Supported Real-Time Data Processing Using Internet of Things Sensor Technology},

author = {Alexander Arntz and Felix Adler and Dennis Kitzmann and Sabrina C. Eimler},

editor = {Norbert A. Streitz and Shin'ichi Konomi},

isbn = {978-3-031-05431-0},

year  = {2022},

date = {2022-01-01},

booktitle = {Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity},

pages = {3--17},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {Internet of things (IoT) devices increasingly permeate everyday life and provide vital and convenient information. Augmented reality (AR) enables the embedding of this information in the environment using visualizations that can contextualize data for various applications such as Smart Home. Current applications providing a visual representation of the information are often limited to graphs or bar charts, neglecting the variety of possible coherence between the subject and the visualization. We present a setup for real-time AR-based visualizations of data collected by IoT devices. Three distinct battery-powered IoT microcontroller systems were designed and programmed. Each is outfitted with numerous sensors, i.e. for humidity or temperature, to interact with the developed AR application through a network connection. The AR application was developed using Unity3D and the Vuforia AR SDK for Android-based mobile devices with the goal of providing processed and visualized information that is comprehensible for the respective context. Inspired by weather applications for mobile devices, the visualization contains animated dioramas, with changing attributes based on the input data from the IoT microcontroller. This work contains the configuration of the IoT microcontroller hardware, the network interface used, the development process of the AR application, and its usage, complemented by possible future extensions described in an outlook.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-031-06509-5_14,

title = {Augmented-Reality-Based Real-Time Patient Information for Nursing},

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

editor = {Sakae Yamamoto and Hirohiko Mori},

isbn = {978-3-031-06509-5},

year  = {2022},

date = {2022-01-01},

booktitle = {Human Interface and the Management of Information: Applications in Complex Technological Environments},

pages = {195--208},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {While the usage of digital systems in the medical sector has increased, nursing activities are still mostly performed without any form of digital assistance. Considering the complex and demanding procedures the medical personnel is confronted with, a high task load is expected which is prone to human errors. Solutions, however, need to match staff requirements and ideally involve them in the development process to ensure acceptance and usage. Based on desired application scenarios, we introduce a concept of an augmented reality (AR)-based patient data application that provides context-relevant information for nursing staff and doctors. Developed for the Hololens 2, the application allows the retrieval and synchronization of the patient data from the host network of the respective hospital information system. For this purpose, a system infrastructure consisting of several software components was developed to simulate the exchange between the AR device and the independent hospital environment. The paper outlines the conceptual approach based on requirements collected from nurses, related work, the technical implementation and discusses limitations and future developments.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3491101.3519786,

title = {What Are You Grateful for? - Enhancing Gratitude Routines by Using Speech Assistants},

author = {André Helgert and Carolin Straßmann},

url = {https://doi.org/10.1145/3491101.3519786},

doi = {10.1145/3491101.3519786},

isbn = {9781450391566},

year  = {2022},

date = {2022-01-01},

booktitle = {Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems},

publisher = {Association for Computing Machinery},

address = {New Orleans, LA, USA},

series = {CHI EA '22},

abstract = {This paper presents an extension for Amazon’s Alexa, which provides a gratitude journal, and investigates its effectiveness compared to a regular paper-based version. Decades of research demonstrate that expressing gratitude has various psychological and physical benefits. At the same time, gratitude routines run the risk of being a hassle activity, which diminishes the positive outcome. Speech assistants might help to integrate gratitude routines more easily in an intuitive way using voice input. The results of our 8-day field study with two experimental groups (Alexa group vs. Paper group},

keywords = {Alexa, Gratitude Journal, Gratitude Routines, Speech Assistant},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{grunOffPolicyContinuousControl2021b,

title = {Off-Policy Continuous Control Using Distributional Reinforcement Learning},

author = {Felix Grün and Tobias Glasmachers and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p001},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

publisher = {Bernstein Conference},

keywords = {Machine Learning, Reinforcement learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lehmlerTransferLearningPatientSpecific2021b,

title = {Transfer-Learning for Patient Specific Model Re-Calibration: Application to sEMG-Classification},

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

doi = {10.12751/nncn.bc2021.p005},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

publisher = {Bernstein Conferen},

keywords = {BCI, Computational Complexity, Deep Transfer-Learning, Machine Learning, transfer learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schmidtArtificiallyGeneratedMuscle2021b,

title = {Artificially Generated Muscle Signals},

author = {Marie Dominique Schmidt and Tobias Glasmachers and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p111},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

publisher = {Bernstein Conference},

keywords = {BCI, Machine Learning, movement model, muscle signal generator, recurrent neural network},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sziburisModellingGenerationHuman2021b,

title = {Modelling the Generation of Human Upper-Limb Reaching Trajectories: An Extended Behavioural Attractor Dynamics Approach},

author = {Tim Sziburis and Susanne Blex and Tobias Glasmachers and Inaki Rano and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p078},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

publisher = {Bernstein Conference},

keywords = {attractor dynamics approach, human arm motion},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{xavierfidencioErrorCorrectionIntegration2021b,

title = {Beyond Error Correction: Integration of Error-Related Potentials into Brain-Computer Interfaces for Improved Performance},

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

doi = {10.12751/nncn.bc2021.p163},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

publisher = {Bernstein Conference},

keywords = {BCI, error-related potentials, Machine Learning, Reinforcement learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{grunOffPolicyContinuousControl2021,

title = {Off-Policy Continuous Control Using Distributional Reinforcement Learning},

author = {Felix Grün and Tobias Glasmachers and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p001},

year  = {2021},

date = {2021-09-15},

urldate = {2021-09-15},

booktitle = {BC21 : Computational Neuroscience & Neurotechnology Bernstein Conference 2021},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {Machine Learning, Reinforcement learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{lehmlerTransferLearningPatientSpecific2021,

title = {Transfer-Learning for Patient Specific Model Re-Calibration: Application to sEMG-Classification},

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

doi = {10.12751/nncn.bc2021.p005},

year  = {2021},

date = {2021-09-15},

urldate = {2021-09-15},

booktitle = {BC21 : Computational Neuroscience & Neurotechnology Bernstein Conference 2021},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{schmidtArtificiallyGeneratedMuscle2021,

title = {Artificially Generated Muscle Signals},

author = {Marie Dominique Schmidt and Tobias Glasmachers and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p111},

year  = {2021},

date = {2021-09-15},

urldate = {2021-09-15},

booktitle = {BC21 : Computational Neuroscience & Neurotechnology Bernstein Conference 2021},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{sziburisModellingGenerationHuman2021,

title = {Modelling the Generation of Human Upper-Limb Reaching Trajectories: An Extended Behavioural Attractor Dynamics Approach},

author = {Tim Sziburis and Susanne Blex and Tobias Glasmachers and Inaki Rano and Ioannis Iossifidis},

doi = {10.12751/nncn.bc2021.p078},

year  = {2021},

date = {2021-09-15},

urldate = {2021-09-15},

booktitle = {BC21 : Computational Neuroscience & Neurotechnology Bernstein Conference 2021},

publisher = {BCCN Bernstein Network Computational Network},

keywords = {BCI, Machine Learning, movement model},

pubstate = {published},

tppubtype = {inproceedings}

}