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Virtual Reality Self Co-Embodiment: An Alternative to Mirror Therapy for Post-Stroke Upper Limb Rehabilitation

IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第5期30卷 2390-2399页

作者： Curiel, Rodrigo Cerecero Nakamura, Takuto Kuzuoka, Hideaki Kanaya, Takafumi Prahm, Cosima Matsumoto, Keigo Univ Tokyo Tokyo Japan Med Univ Vienna Vienna Austria

We present Virtual Reality Self Co-embodiment, a new method for post-stroke upper limb rehabilitation. It is inspired by mirror therapy, where the patient's healthy arm is involved in recovering the affected arm's motion. By tracking the user's head, wrists, and fingers' positions, our new approach allows the handicapped arm to control a digital avatar in order to pursue a reaching task. We apply the concept of virtual co-embodiment to use the information from the unaffected arm and complete the affected limb's impaired motion, which is our added unique feature. This requires users to mechanically involve the incapacitated area as much as possible, prioritizing actual movement rather than the sole imagination of it. As a result, subjects will see a seemingly normally functional virtual arm primarily controlled by their handicapped extremity, but with the constant support of their healthy limb's motion. Our experiment compares the task execution performance and embodiment perceived when interacting with both mirror therapy and our proposed technique. We found that our approach's provided sense of ownership is mildly impacted by users' motion planning response times, which mirror therapy does not exhibit. We also observed that mirror therapy's sense of ownership is moderately affected by the subject's proficiency while executing the assigned task, which our new method did not display. The results indicate that our proposed method provides similar embodiment and rehabilitation capabilities to those perceived from existing mirror therapy. This experiment was performed in healthy individuals to have an unbiased comparison of how mirror therapy's and VRSelfCo's task performance and degree of virtual embodiment compare, but future work explores the possibility of applying this new approach to actual post-stroke patients.

关键词： human-centered computing user interfaces virtual reality rehabilitation techniques virtual embodiment stroke recovery motor imagery

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A Visual Interface for Exploring Hypotheses About Neural Circuits

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第7期30卷 3945-3958页

作者： Vohra, Sumit Kumar Harth, Philipp Isoe, Yasuko Bahl, Armin Fotowat, Haleh Engert, Florian Hege, Hans-Christian Baum, Daniel Zuse Inst Berlin ZIB Dept Visual & Data Ctr Comp D-14195 Berlin Germany Harvard Univ Dept Mol & Cellular Biol Cambridge MA 02138 USA Univ Konstanz Ctr Adv Study Collect Behav D-78464 Constance Germany

One of the fundamental problems in neurobiological research is to understand how neural circuits generate behaviors in response to sensory stimuli. Elucidating such neural circuits requires anatomical and functional information about the neurons that are active during the processing of the sensory information and generation of the respective response, as well as an identification of the connections between these neurons. With modern imaging techniques, both morphological properties of individual neurons as well as functional information related to sensory processing, information integration and behavior can be obtained. Given the resulting information, neurobiologists are faced with the task of identifying the anatomical structures down to individual neurons that are linked to the studied behavior and the processing of the respective sensory stimuli. Here, we present a novel interactive tool that assists neurobiologists in the aforementioned tasks by allowing them to extract hypothetical neural circuits constrained by anatomical and functional data. Our approach is based on two types of structural data: brain regions that are anatomically or functionally defined, and morphologies of individual neurons. Both types of structural data are interlinked and augmented with additional information. The presented tool allows the expert user to identify neurons using Boolean queries. The interactive formulation of these queries is supported by linked views, using, among other things, two novel 2D abstractions of neural circuits. The approach was validated in two case studies investigating the neural basis of vision-based behavioral responses in zebrafish larvae. Despite this particular application, we believe that the presented tool will be of general interest for exploring hypotheses about neural circuits in other species, genera and taxa.

关键词： Neurons Neural circuits Visualization Imaging Image reconstruction Behavioral sciences Data visualization human-centered computing scientific visualization visualization systems and tools web-based interaction

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Integrating Heterogeneous VR Systems Into Physical Space for Collaborative Extended Reality

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IEEE ACCESS 2024年 12卷 9848-9859页

作者： An, Jaepung Lee, Joo Ho Park, Sanghun Ihm, Insung Sogang Univ Dept Comp Sci & Engn Seoul 04107 South Korea Sogang Univ Grad Sch Metaverse Seoul 04107 South Korea

Virtual reality(VR) applications are typically developed within their own immersive digital worlds;therefore, virtual spaces are usually treated as discrete from the physical space where augmented and mixed reality users exist, which makes it difficult to combine these heterogeneous realities into an integrated extended reality(XR) environment. Along these lines, we propose a method that enables a user to geometrically register the virtual space within a VR application to a real space using a commodity camera in a workspace as an anchor point. We first investigate the mathematical aspect of the computational model for connecting the virtual space to the physical world. Then, we present a computational procedure that implements our proposed method with numerical accuracy and stability. As an application, we demonstrate that users of two VR systems from different vendors may collaborate within a shared real workspace while interacting with each other physically. The presented method provides a key mechanism for enabling XR users to leverage these immersive technologies by effectively using different realities within an integrated environment.

关键词： Aerospace electronics Cameras Three-dimensional displays X reality Robot sensing systems Mathematical models Calibration human-centered computing human-computer interaction (HCI) interaction paradigms virtual reality

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Synergistic grasp analysis: A cross-sectional exploration using a multi-sensory data glove

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WEARABLE TECHNOLOGIES 2025年 6卷 e2-e2页

作者： Pratap, Subhash Ito, Kazuaki Hazarika, Shyamanta M. IIT Guwahati Biomimet Robot & AI Lab Mech Engn Gauhati Assam India Gifu Univ Dept Intelligent Mech Engn Gifu Japan

This paper investigates hand grasping, a fundamental activity in daily living, by examining the forces and postures involved in the lift-and-hold phases of grasping. We introduce a novel multi-sensory data glove, integrated with resistive flex sensors and capacitive force sensors, to measure the intricate dynamics of hand movement. The study engaged five subjects to capture a comprehensive dataset that includes contact forces at the fingertips and joint angles, furnishing a detailed portrayal of grasp mechanics. Focusing on grasp synergies, our analysis delved into the quantitative relationships between the correlated forces among the fingers. By manipulating one variable at a time-either the object or the subject-our cross-sectional approach yields rich insights into the nature of grasp forces and angles. The correlation coefficients for finger pairs presented median values ranging from 0.5 to nearly 0.9, indicating varying degrees of inter-finger coordination, with the thumb-index and index-middle pairs exhibiting particularly high synergy. The findings, depicted through spider charts and correlation coefficients, reveal significant patterns of cooperative finger behavior. These insights are crucial for the advancement of hand mechanics understanding and have profound implications for the development of assistive technologies and rehabilitation devices.

关键词： grasp synergies multi-sensory data glove human-centered computing

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Dancing in virtual reality as an inclusive platform for social and physical fitness activities: a survey

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VISUAL COMPUTER 2024年第6期40卷 4055-4070页

作者： Sarupuri, Bhuvaneswari Kulpa, Richard Aristidou, Andreas Multon, Franck Univ Rennes CNRS INRIA IRISA Rennes France Univ Rennes M2S Rennes France Univ Cyprus CY-1678 Nicosia Cyprus

Virtual reality (VR) has recently seen significant development in interaction with computers and the visualization of information. More and more people are using virtual and immersive technologies in their daily lives, especially for entertainment, fitness, and socializing purposes. This paper presents a qualitative evaluation of a large sample of users using a VR platform for dancing (N = 292);we study the users' motivations, experiences, and requirements for using VR as an inclusive platform for dancing, mainly as a social or physical activity. We used an artificial intelligence platform (OpenAI) to extract categories or clusters of responses automatically. We organized the data into six user motivation categories: fun, fitness, social activity, pandemic, escape from reality, and professional activities. Our results indicate that dancing in virtual reality is a different experience than in the real world, and there is a clear distinction in the user's motivations for using VR platforms for dancing. Our survey results suggest that VR is a tool that can positively impact physical and mental well-being through dancing. These findings complement the related work, help in identifying the use cases, and can be used to assist future improvements of VR dance applications.

关键词： human-centered computing Virtual reality Dancing Social platforms OpenAI

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Trust dynamics in human interaction with an industrial robot

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BEHAVIOUR & INFORMATION TECHNOLOGY 2025年第2期44卷 266-288页

作者： Alhaji, Basel Buettner, Sebastian Sanjay Kumar, Shushanth Prilla, Michael Univ Duisburg Essen Fac Comp Sci Dept Human Centered Comp & Cognit Sci HCCS Interact Syst Duisburg Germany Tech Univ Clausthal Human Centered Informat Syst Clausthal Zellerfeld Germany Univ Duisburg Essen Fac Comp Sci Dept Human Centered Comp & Cognit Sci HCCS Interact Syst D-47057 Duisburg Germany

Trust is important for collaboration. In hybrid teams of humans and robots, trust enables smooth collaboration and reduces risks. Just as collaboration between humans and robots differs from interpersonal collaboration, so does the nature of trust in human-robot interaction (HRI). Therefore, further investigations on trust formation and dissolution in HRI, factors affecting it, and means for keeping trust on an appropriate level are needed. However, our knowledge of interpersonal trust and trust in autonomous agents cannot be transferred directly to HRI. In this paper, we present a study with 32 participants on trust formation and dissolution as well as forecasting to influence trust in an industry robot. Results show differences in dynamics and factors of trust formation and dissolution. Additionally, we find that the effect of forecasting on trust depends on task success. These findings support the design of trustful human-robot interaction and corresponding robotic team members.

关键词： human-centered computing human computer interaction (HCI) Empirical studies in HCI human-Robot Interaction Industrial Robot Trust Trust Dynamics Collaboration

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Heuristics for evaluating narrative visualization: a validation study

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JOURNAL OF VISUALIZATION 2025年第3期28卷 645-659页

作者： Errey, Nina Zowghi, Didar Leong, Tuck Wah Wu, Yadong Yuan, Xiaoru Huang, Weidong Liang, Christy Jie UTS Sch Comp Sci Sydney NSW Australia CSIRO Data61 Sydney Australia RMIT Sch Comp Technol Melbourne Australia Sichuan Univ Sci & Engn Comp Sci & Engn Yibin Peoples R China Peking Univ Sch Intelligence Sci & Technol Beijing Peoples R China UTS Transdisciplinary Sch Sydney Australia

Narrative visualization integrates data visualization and narrative techniques to convey a compelling story. Narrative visualization is notoriously difficult to evaluate. One solution is heuristic evaluation, using a domain-specific set of heuristics. This paper validates a set of heuristics proposed specifically for evaluating narrative visualization. We conducted studies with experienced narrative visualization practitioners in both summative and formative settings. We found that the set of heuristics showed promise in a summative setting, where similar responses evidenced that the set of heuristics could provide reliable evaluation metrics. Furthermore, in a formative setting, implementing the set of heuristics was reported to be useful in the design process;however, due to their limited focus, we recommend that it be implemented in conjunction with other evaluation guidelines.

关键词： human-centered computing Information visualization Visualization Visualization application domains Empirical studies in visualization

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Layout-Agnostic human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2025年第1期9卷 1-38页

作者： Thukral, Megha Dhekane, Sourish gunesh Hiremath, Shruthi k. Haresamudram, Harish Ploetz, Thomas Georgia Inst Technol Sch Interact Comp Atlanta GA 30332 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA USA

human activity recognition (HAR) using ambient sensors in smart homes has numerous applications for human healthcare and wellness. However, building general-purpose HAR models that can be deployed to new smart home environments requires a significant amount of annotated sensor data and training overhead. Most smart homes vary significantly in their layouts, i.e., floor plans and the specifics of sensors embedded, resulting in low generalizability of HAR models trained for specific homes. We address this limitation by introducing a novel, layout-agnostic modeling approach for HAR systems in smart homes that utilizes the transferrable representational capacity of natural language descriptions of raw sensor data. To this end, we generate Textual Descriptions Of Sensor Triggers (TDOST) that encapsulate the surrounding trigger conditions and provide cues for underlying activities to the activity recognition models. Leveraging textual embeddings, rather than raw sensor data, we create activity recognition systems that predict standard activities across homes without (re-)training or adaptation to target homes. Through an extensive evaluation, we demonstrate the effectiveness of TDOST-based models in unseen smart homes through experiments on benchmark Orange4Home and CASAS datasets. Furthermore, we conduct a detailed analysis of how the individual components of our approach affect downstream activity recognition performance.

关键词： human-centered computing Ubiquitous and mobile computing Empirical studies in ubiquitous and mobile computing computing methodologies Machine learning

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Efficient Decoding of Affective States from Video-elicited EEG Signals: An Empirical Investigation

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ACM TRANSACTIONS ON MULTIMEDIA computing COMMUNICATIONS AND APPLICATIONS 2024年第10期20卷 1-24页

作者： Latifzadeh, Kayhan Gozalpour, Nima Traver, V. Javier Ruotsalo, Tuukka Kawala-Sterniuk, Aleksandra Leiva, Luis A. Univ Luxembourg Esch Sur Alzette Luxembourg Univ Jaume 1 INIT Castellon de la Plana Spain Univ Copenhagen Copenhagen Denmark LUT Univ Lahti Finland Opole Univ Technol Opole Poland

Affect decoding through brain-computer interfacing (BCI) holds great potential to capture users' feelings and emotional responses via non-invasive electroencephalogram (EEG) sensing. Yet, little research has been conducted to understand efficient decoding when users are exposed to dynamic audiovisual contents. In this regard, we study EEG-based affect decoding from videos in arousal and valence classification tasks, considering the impact of signal length, window size for feature extraction, and frequency bands. We train both classic Machine Learning models (SVMs and k-NNs) and modern Deep Learning models (FCNNs and GTNs). Our results show that: (1) affect can be effectively decoded using less than 1 minute of EEG signal;(2) temporal windows of 6 and 10 seconds provide the best classification performance for classic Machine Learning models but Deep Learning models benefit from much shorter windows of 2 seconds;and (3) any model trained on the Beta band alone achieves similar (sometimes better) performance than when trained on all frequency bands. Taken together, our results indicate that affect decoding can work in more realistic conditions than currently assumed, thus becoming a viable technology for creating better interfaces and user models.

关键词： human-centered computing User models Ambient intelligence computing methodologies Machine learning approaches

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What I Don't Like about You?: A Systematic Review of Impeding Aspects for the Usage of Conversational Agents

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INTERACTING WITH COMPUTERS 2024年第5期36卷 293-312页

作者： Hennekeuser, Darius Vaziri, Daryoush Golchinfar, David Stevens, Gunnar Univ Appl Sci Bonn Rhein Sieg Dept Business Adm Grantham-Allee 20 D-53757 St Augustin Germany Univ Siegen Dept IT Secur Adolf Reichwein Str 2a D-57076 Siegen Germany

The application and use cases for conversational agents (CAs) are versatile. Smart speakers such as Alexa and Google Home are used in smart home environments, digital agents are integrated into car systems and chatbots are increasingly used in customer service processes. However, human-computer interaction researchers identify and investigate a wide-ranging variety of aspects impeding the usage of CAs by end-users. In general, impediments differ depending on use case contexts, user group characteristics and the CA's technological infrastructure. Hence, it is difficult and often ambiguous for designers and developers to generate an appropriate awareness about aspects impeding CA usage. We address this problem, by conducting a systematic review of 65 publications surveying impeding aspects of the usage of CAs.

关键词： human computer interaction (HCI) HCI design and evaluation methods interaction design human-centered computing natural language interfaces

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