ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted TrainingProlonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive systems. Existing posture sensing methods such as vision-based or wearable approaches face limitations including occlusion, privacy concerns, user discomfort, and restricted deployment flexibility. We introduce ChairPose, the first full body, wearable free seated pose estimation system that relies solely on pressure sensing and operates independently of chair geometry. ChairPose employs a two stage generative model trained on pressure maps captured from a thin, chair agnostic sensing mattress. Unlike prior approaches, our method explicitly incorporates chair morphology into the inference process, enabling accurate, occlusion free, and privacy preserving pose estimation. To support generalization across diverse users and chairs, we introduce a physics driven data augmentation pipeline that simulates realistic variations in posture and seating conditions. Evaluated across eight users and four distinct chairs, ChairPose achieves a mean per joint position error of 89.4 mm when both the user and the chair are unseen, demonstrating robust generalization to novel real world generalizability. ChairPose expands the design space for posture aware interactive systems, with potential applications in ergonomics, healthcare, and adaptive user interfaces. All code and data are publicly available on Kaggle at https://www.kaggle.com/datasets/lalaray/chairpose.2025LRLala Shakti Swarup Ray et al.Human Pose & Activity RecognitionBiosensors & Physiological MonitoringUIST
The Impact of Observer Presence on Trainees' Mental States and Performance in Remote Military Training with Virtual Humans in Mixed Reality EnvironmentRemote, vs. in situ, instruction may be regarded to decrease trainee engagement and concentration, potentially reducing training effectiveness. As such, local evaluative observers are often deployed to create the situated atmosphere. However, these observers can also have a negative effect on the trainees' mental state and performance. This study investigates the impact of a local human observer's presence on trainees' mental state and task performance during military training conducted in a mixed reality (MR) environment, where a tele-presence avatar, controlled by the remote instructor, leads the training. An experiment was conducted comparing three conditions: remote training with (1) no observer, (2) a real observer, and (3) a virtual observer. The study found that although the observer, real or virtual, indeed negatively impacted the trainee's mental state, the remote trainer avatar helped maintain the immersion/concentration, ensuring the trainees achieved the performance comparable to the no observer condition.2025JPJunSeo Park et al.Korea University, Digital Experience LaboratoryImmersion & Presence ResearchTeleoperation & TelepresenceCHI
MagPie: Extending a Smartphone’s Interaction Space via a Customizable Magnetic Back-of-Device Input AccessoryBack-of-Device (BoD) interfaces have emerged as a promising solution to free up screen real estate in smartphones by offloading interactions from the display to the back, thereby reducing reliance on on-screen interfaces. However, existing BoD solutions face limitations, such as requiring specialized hardware, consuming excessive power, or offering limited input vocabularies. We introduce MagPie, a novel BoD interface that leverages the magnetic phenomenon induced by MagSafe, part of the wireless charging standard. Users can seamlessly attach MagPie to MagSafe-enabled smartphones and interact using tangible, modular interfaces that generate unique magnetic signals upon activation. MagPie then detects these signals and recognizes the input through magnetic sensing. Our experiments with real-world users demonstrate that i) MagPie achieves high performance in accuracy, usability, deployability, responsiveness, and robustness across diverse environments, and ii) its tangible, intuitive, and customizable design opens up possibilities for a whole new class of smartphone interaction scenarios.2025IKInsu Kim et al.Chung-Ang University, Department of Smart CitiesShape-Changing Interfaces & Soft Robotic MaterialsContext-Aware ComputingCHI
The Effects of False but Stable Heart Rate Feedback on Cybersickness and User Experience in Virtual RealityVirtual reality (VR) offers a compelling and immersive experience; however, cybersickness (or VR sickness) stands as a significant obstacle to its widespread adoption. When a user experiences cybersickness, one's physical condition deteriorates with various symptoms, often accompanied by an increased and destabilized heart rate and even altered perception of one's state. In this paper, we propose to provide ``False but Stable Heart rate (FSH)'' feedback through auditory and vibrotactile stimulation to reversely induce a stably perceived heart rate and, thereby, alleviate cybersickness while navigating a sickness-inducing VR content. The validation of the human experiment confirmed the intended effect in a statistically significant way. Furthermore, it was found that the lesser compatible FSH feedback had a more substantial sickness reduction effect but distracted the user with the reduced immersive experience. The compatible FSH feedback still showed moderate sickness reduction with the maintained sense of presence and immersion.2024DJDongYun Joo et al.Korea UniversityMotion Sickness & Passenger ExperienceCHI
Engaged and Affective Virtual Agents: Their Impact on Social Presence, Trustworthiness, and Decision-Making in the Group DiscussionThis study investigates how different virtual agent (VA) behaviors influence subjects' perceptions and group decision-making. Participants carried out experimental group discussions with a VA exhibiting varying levels of engagement and affective behavior. Engagement refers to the VA's focus on the group task, whereas affective behavior reflects the VA's emotional state. The findings revealed that VA's engagements effectively captured participants' attention even in the group setting and enhanced group synergy, thereby facilitating more in-depth discussion and producing better consensus. On the other hand, VA's affective behavior negatively affected the perceived social presence and trustworthiness. Consequently, in the context of group discussion, participants preferred the engaged and non-affective VA to the non-engaged and affective VA. The study provides valuable insights for improving the VA's behavioral design as a team member for collaborative tasks.2024HKHanseob Kim et al.Korea University, Korea Institute of Science and TechnologyConversational ChatbotsAgent Personality & AnthropomorphismCHI
Mixing in Reverse Optical Flow to Mitigate Vection and Simulation Sickness in Virtual RealitySimulator sickness has been one of the major obstacles toward making virtual reality (VR) widely accepted and used. For example, virtual navigation produces vection, which is the illusion of self-motion as one perceives bodily motion despite no movement actually occurs. This, in turn, causes a sensory conflict between visual and actual (or vestibular) motion and sickness. In this study, we explore a method to reduce simulator sickness by visually mixing the optical flow patterns that are in the reverse direction of the virtual visual motion. As visual motion is mainly detected and perceived by the optical flow, artificial mixing in the reverse flow is hypothesized to induce a cancellation effect, thereby reducing the degree of the conflict with the vestibular sense and sickness. To validate our hypothesis, we developed a real-time algorithm to visualize the reverse optical flow and conducted experiments by comparing the before and after sickness levels in seven virtual navigation conditions. The experimental results confirmed the proposed method was effective for reducing the simulator sickness in a statistically significant manner. However, no dependency to the motion type or degrees of freedom were found. Significant distraction and negative influence to the sense of presence and immersion were observed only when the the artificially added reverse optical flow patterns were rather visually marked with high contrast to the background content.2022SPSu Han Park et al.Korea UniversityMotion Sickness & Passenger ExperienceImmersion & Presence ResearchCHI
Love in Lyrics: An Exploration of Supporting Textual Manifestation of Affection in Social MessagingAffectionate communication, the conveyance of closeness, care, and fondness for another, plays a key role in romantic relationships. While the pervasive use of digital technology for communication limits affectionate interaction through nonverbal cues - a major channel of expression in face-to-face settings, there have been few approaches which scaffold couples' romantic text conversations. To bridge this gap, we propose a novel interactive system Lily which gives users inspirations to enrich their romantic expressions in text messaging. It first listens to users' original input and then recommends romantic lyrics holding the closest meaning in real-time during chats with partners. After a three-day empirical study, participants who are real-life couples reported that they not only received useful cues from Lily in terms of how to polish their affectionate expressions, but also learnt to enrich the conversation with topics enlightened by its recommendations. Based on our findings, we finally provide several design considerations for actual deployment of such an application.2019TKTaewook Kim et al.Language and Expressivity ICSCW
AILA: Attentive Interactive Labeling Assistant for Document Classification through Attention-Based Deep Neural NetworksDocument labeling is a critical step in building various machine learning applications. However, the step can be time-consuming and arduous, requiring a significant amount of human efforts. To support an efficient document labeling environment, we present a system called Attentive Interactive Labeling Assistant (AILA). In its core, AILA uses Interactive Attention Module (IAM), a novel module that visually highlights words in a document that labelers may pay attention to when labeling a document. IAM utilizes attention-based Deep Neural Networks which not only support a prediction of which words to highlight but also enable labelers to indicate words that should be assigned a high attention weight while labeling to improve the future quality of word prediction.We evaluated the labeling efficiency and the accuracy by comparing the conditions with and without IAM in our study. The results showed that participants' labeling efficiency increased significantly under the condition with IAM than the condition without IAM, while the two conditions maintained roughly the same labeling accuracy.2019MCMinsuk Choi et al.Korea UniversityHuman-LLM CollaborationUser Research Methods (Interviews, Surveys, Observation)CHI
Voice Presentation Attack Detection through Text-Converted Voice Command AnalysisVoice assistants are quickly being upgraded to support advanced, security-critical commands such as unlocking devices, checking emails, and making payments. In this paper, we explore the feasibility of using users' text-converted voice command utterances as classification features to help identify users' genuine commands, and detect suspicious commands. To maintain high detection accuracy, our approach starts with a globally trained attack detection model (immediately available for new users), and gradually switches to a user-specific model tailored to the utterance patterns of a target user. To evaluate accuracy, we used a real-world voice assistant dataset consisting of about 34.6 million voice commands collected from 2.6 million users. Our evaluation results show that this approach is capable of achieving about 3.4% equal error rate (EER), detecting 95.7% of attacks when an optimal threshold value is used. As for those who frequently use security-critical (attack-like) commands, we still achieve EER below 5%.2019IKIl-Youp Kwak et al.Samsung ResearchIntelligent Voice Assistants (Alexa, Siri, etc.)Voice AccessibilityDeepfake & Synthetic Media DetectionCHI
Flotation Simulation in a Cable-driven Virtual Environment – A Study with ParasailingThis paper presents flotation simulation in a cable-driven virtual environment. For this, a virtual parasailing system was developed, where the visual stimulus was provided through a VR headset and the physical stimulus was given by wires. In order to prevent the user from moving out of the limited workspace of the cable-driven system, the visual acceleration was washout-filtered to produce the physical acceleration. In the parasailing trajectory, we focused on the stages of vertical acceleration/deceleration and conducted an experiment to identify how much gain can be applied to the visual acceleration, which makes the user feel the natural self-motion when integrated with physical stimulus. Then, the results were tested using several types of full-course virtual parasailing. The results showed that fairly large differences between visual and physical stimuli would be accepted and different gains could be assigned depending on the user’s altitudes.2018HKHyeongYeop Kang et al.Korea UniversityElectrical Muscle Stimulation (EMS)Full-Body Interaction & Embodied InputCHI
TopicOnTiles: Tile-Based Spatio-Temporal Event Analytics via Exclusive Topic Modeling on Social MediaDetecting anomalous events of a particular area in a timely manner is an important task. Geo-tagged social media data are useful resource for this task; however, the abundance of everyday language in them makes this task still challenging. To address such challenges, we present TopicOnTiles, a visual analytics system that can reveal information relevant to anomalous events in a multi-level tile-based map interface by using social media data. To this end, we adopt and improve a recently proposed topic modeling method that can extract spatio-temporally exclusive topics corresponding to a particular region and a time point. Furthermore, we utilize a tile-based map interface to efficiently handle large-scale data in parallel. Our user interface effectively highlights anomalous tiles using our novel glyph visualization that encodes the degree of anomaly computed by our exclusive topic modeling processes. To show the effectiveness of our system, we present several usage scenarios using real-world datasets as well as comprehensive user study results.2018MCMinsuk Choi et al.Korea UniversityInteractive Data VisualizationGeospatial & Map VisualizationUser Research Methods (Interviews, Surveys, Observation)CHI