Giulia Barbareschi, Songchen Zhou, Ando Ryoichi, Midori Kawaguchi, Mark Armstrong, Mikito Ogino, Shunsuke Aoiki, Eisaku Ohta, Harunobu Taguchi, Youichi Kamiyama, Masatane Muto, Kentaro Yoshifuji, and Kouta Minamizawa. 2024. Brain Body Jockey project: Transcending Bodily Limitations in Live Performance via Human Augmentation. In Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '24). Association for Computing Machinery, New York, NY, USA, Article 18, 1–14. https://doi.org/10.1145/3663548.3675621

Musicians with significant mobility limitations, face unique challenges in being able to use their bodies to interact with fans during live performances. In this paper we present the results of a collaboration between a professional DJ with advanced Amyotrophic Lateral Sclerosis and a group of technologists and researchers culminating in two public live performances leveraging human augmentation technologies to enhance the artist’s stage presence. Our system combines Brain Machine Interface, and accelerometer based trigger, to select pre-programmed moves performed by robotic arms during a live event, as well as for facilitating direct physical interaction during a “Meet the DJ” event. Our evaluation includes ethnographic observations and interviews with the artist and members of the audience. Results show that the system allowed artist and audience to feel a sense of unity, expanded the imagination of creative possibilities, and challenged conventional perceptions of disability in the arts and beyond.

https://dl.acm.org/doi/10.1145/3663548.3675621

F. Chiossi, I. Trautmannsheimer, C. Ou, U. Gruenefeld and S. Mayer, "Searching Across Realities: Investigating ERPs and Eye-Tracking Correlates of Visual Search in Mixed Reality," in IEEE Transactions on Visualization and Computer Graphics, vol. 30, no. 11, pp. 6997-7007, Nov. 2024, doi: 10.1109/TVCG.2024.3456172.

Mixed Reality allows us to integrate virtual and physical content into users' environments seamlessly. Yet, how this fusion affects perceptual and cognitive resources and our ability to find virtual or physical objects remains uncertain. Displaying virtual and physical information simultaneously might lead to divided attention and increased visual complexity, impacting users' visual processing, performance, and workload. In a visual search task, we asked participants to locate virtual and physical objects in Augmented Reality and Augmented Virtuality to understand the effects on performance. We evaluated search efficiency and attention allocation for virtual and physical objects using event-related potentials, fixation and saccade metrics, and behavioral measures. We found that users were more efficient in identifying objects in Augmented Virtuality, while virtual objects gained saliency in Augmented Virtuality. This suggests that visual fidelity might increase the perceptual load of the scene. Reduced amplitude in distractor positivity ERP, and fixation patterns supported improved distractor suppression and search efficiency in Augmented Virtuality. We discuss design implications for mixed reality adaptive systems based on physiological inputs for interaction.

https://ieeexplore.ieee.org/document/10679197

S. Cheng, Y. Liu, Y. Gao and Z. Dong, "“As if it were my own hand”: inducing the rubber hand illusion through virtual reality for motor imagery enhancement," in IEEE Transactions on Visualization and Computer Graphics, vol. 30, no. 11, pp. 7086-7096, Nov. 2024, doi: 10.1109/TVCG.2024.3456147

Brain-computer interfaces (BCI) are widely used in the field of disability assistance and rehabilitation, and virtual reality (VR) is increasingly used for visual guidance of BCI-MI (motor imagery). Therefore, how to improve the quality of electroencephalogram (EEG) signals for MI in VR has emerged as a critical issue. People can perform MI more easily when they visualize the hand used for visual guidance as their own, and the Rubber Hand Illusion (RHI) can increase people's ownership of the prosthetic hand. We proposed to induce RHI in VR to enhance participants' MI ability and designed five methods of inducing RHI, namely active movement, haptic stimulation, passive movement, active movement mixed with haptic stimulation, and passive movement mixed with haptic stimulation, respectively. We constructed a first-person training scenario to train participants' MI ability through the five induction methods. The experimental results showed that through the training, the participants' feeling of ownership of the virtual hand in VR was enhanced, and the MI ability was improved. Among them, the method of mixing active movement and tactile stimulation proved to have a good effect on enhancing MI. Finally, we developed a BCI system in VR utilizing the above training method, and the performance of the participants improved after the training. This also suggests that our proposed method is promising for future application in BCI rehabilitation systems.

https://ieeexplore.ieee.org/document/10669780

Pavel Manakhov, Ludwig Sidenmark, Ken Pfeuffer, and Hans Gellersen. 2024. Filtering on the Go: Effect of Filters on Gaze Pointing Accuracy During Physical Locomotion in Extended Reality. IEEE Transactions on Visualization and Computer Graphics 30, 11 (Nov. 2024), 7234–7244. https://doi.org/10.1109/TVCG.2024.3456153

Eye tracking filters have been shown to improve accuracy of gaze estimation and input for stationary settings. However, their effectiveness during physical movement remains underexplored. In this work, we compare common online filters in the context of physical locomotion in extended reality and propose alterations to improve them for on-the-go settings. We conducted a computational experiment where we simulate performance of the online filters using data on participants attending visual targets located in world-, path-, and two head-based reference frames while standing, walking, and jogging. Our results provide insights into the filters' effectiveness and factors that affect it, such as the amount of noise caused by locomotion and differences in compensatory eye movements, and demonstrate that filters with saccade detection prove most useful for on-the-go settings. We discuss the implications of our findings and conclude with guidance on gaze data filtering for interaction in extended reality.

https://ieeexplore.ieee.org/document/10672561

Nicholas Jennings, Han Wang, Isabel Li, James Smith, and Bjoern Hartmann. 2024. What's the Game, then? Opportunities and Challenges for Runtime Behavior Generation. In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST '24). Association for Computing Machinery, New York, NY, USA, Article 106, 1–13. https://doi.org/10.1145/3654777.3676358

Procedural content generation (PCG), the process of algorithmically creating game components instead of manually, has been a common tool of game development for decades. Recent advances in large language models (LLMs) enable the generation of game behaviors based on player input at runtime. Such code generation brings with it the possibility of entirely new gameplay interactions that may be difficult to integrate with typical game development workflows. We explore these implications through GROMIT, a novel LLM-based runtime behavior generation system for Unity. When triggered by a player action, GROMIT generates a relevant behavior which is compiled without developer intervention and incorporated into the game. We create three demonstration scenarios with GROMIT to investigate how such a technology might be used in game development. In a system evaluation we find that our implementation is able to produce behaviors that result in significant downstream impacts to gameplay. We then conduct an interview study with n=13 game developers using GROMIT as a probe to elicit their current opinion on runtime behavior generation tools, and enumerate the specific themes curtailing the wider use of such tools. We find that the main themes of concern are quality considerations, community expectations, and fit with developer workflows, and that several of the subthemes are unique to runtime behavior generation specifically. We outline a future work agenda to address these concerns, including the need for additional guardrail systems for behavior generation.

https://dl.acm.org/doi/10.1145/3654777.3676358

Akifumi Takahashi, Yudai Tanaka, Archit Tamhane, Alan Shen, Shan-Yuan Teng, and Pedro Lopes. 2024. Can a Smartwatch Move Your Fingers? Compact and Practical Electrical Muscle Stimulation in a Smartwatch. In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST '24). Association for Computing Machinery, New York, NY, USA, Article 2, 1–15. https://doi.org/10.1145/3654777.3676373

Smartwatches gained popularity in the mainstream, making them into today’s de-facto wearables. Despite advancements in sensing, haptics on smartwatches is still restricted to tactile feedback (e.g., vibration). Most smartwatch-sized actuators cannot render strong force-feedback. Simultaneously, electrical muscle stimulation (EMS) promises compact force-feedback but, to actuate fingers requires users to wear many electrodes on their forearms. While forearm electrodes provide good accuracy, they detract EMS from being a practical force-feedback interface. To address this, we propose moving the electrodes to the wrist—conveniently packing them in the backside of a smartwatch. In our first study, we found that by cross-sectionally stimulating the wrist in 1,728 trials, we can actuate thumb extension, index extension & flexion, middle flexion, pinky flexion, and wrist flexion. Following, we engineered a compact EMS that integrates directly into a smartwatch’s wristband (with a custom stimulator, electrodes, demultiplexers, and communication). In our second study, we found that participants could calibrate our device by themselves Math 1 faster than with conventional EMS. Furthermore, all participants preferred the experience of this device, especially for its social acceptability & practicality. We believe that our approach opens new applications for smartwatch-based interactions, such as haptic assistance during everyday tasks.

https://dl.acm.org/doi/10.1145/3654777.3676373

Md Touhidul Islam, Noushad Sojib, Imran Kabir, Ashiqur Rahman Amit, Mohammad Ruhul Amin, and Syed Masum Billah. 2024. Wheeler: A Three-Wheeled Input Device for Usable, Efficient, and Versatile Non-Visual Interaction. In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST '24). Association for Computing Machinery, New York, NY, USA, Article 31, 1–20. https://doi.org/10.1145/3654777.3676396

Blind users rely on keyboards and assistive technologies like screen readers to interact with user interface (UI) elements. In modern applications with complex UI hierarchies, navigating to different UI elements poses a significant accessibility challenge. Users must listen to screen reader audio descriptions and press relevant keyboard keys one at a time. This paper introduces Wheeler, a novel three-wheeled, mouse-shaped stationary input device, to address this issue. Informed by participatory sessions, Wheeler enables blind users to navigate up to three hierarchical levels in an app independently using three wheels instead of navigating just one level at a time using a keyboard. The three wheels also offer versatility, allowing users to repurpose them for other tasks, such as 2D cursor manipulation. A study with 12 blind users indicates a significant reduction (40%) in navigation time compared to using a keyboard. Further, a diary study with our blind co-author highlights Wheeler’s additional benefits, such as accessing UI elements with partial metadata and facilitating mixed-ability collaboration.

https://dl.acm.org/doi/10.1145/3654777.3676396

Shwetha Rajaram, Nels Numan, Balasaravanan Thoravi Kumaravel, Nicolai Marquardt, and Andrew D Wilson. 2024. BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI. In Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST '24). Association for Computing Machinery, New York, NY, USA, Article 40, 1–19. https://doi.org/10.1145/3654777.3676326

Today’s video-conferencing tools support a rich range of professional and social activities, but their generic meeting environments cannot be dynamically adapted to align with distributed collaborators’ needs. To enable end-user customization, we developed BlendScape, a rendering and composition system for video-conferencing participants to tailor environments to their meeting context by leveraging AI image generation techniques. BlendScape supports flexible representations of task spaces by blending users’ physical or digital backgrounds into unified environments and implements multimodal interaction techniques to steer the generation. Through an exploratory study with 15 end-users, we investigated whether and how they would find value in using generative AI to customize video-conferencing environments. Participants envisioned using a system like BlendScape to facilitate collaborative activities in the future, but required further controls to mitigate distracting or unrealistic visual elements. We implemented scenarios to demonstrate BlendScape’s expressiveness for supporting environment design strategies from prior work and propose composition techniques to improve the quality of environments.

https://dl.acm.org/doi/10.1145/3654777.3676326