Smell and temperature are tightly intertwined in everyday experience, yet interactive systems often treat them as independent sensory channels. While thermohaptics and olfactory interfaces have been studied separately, it remains unclear how localized nasal thermal stimulation can modulate olfactory perception without changing chemical concentration. We introduce a nose-mounted thermohaptic interface that delivers precise, closed-loop heating and cooling stimuli to the nasal skin area (nasal sidewalls) to modulate olfactory perception. We evaluate our system in two user studies. In the first psychophysical study, we estimate perceptual thresholds (just-noticeable differences, JNDs) for thermally induced changes in perceived odor intensity across three odors, revealing intensity biasing and asymmetric sensitivity between cooling and heating (mean JND: 4.33°C for cooling; 6.15°C for heating). In the second study, we profile odor quality in a structured multidimensional descriptor space, revealing odor-dependent, dimension-specific semantic shifts rather than uniform changes. Together, these findings suggest that nasal thermal modulation can serve as a rapid, reversible, and non-chemical approach for shaping olfactory experience, expanding the design space for perceptually driven olfactory interfaces in multisensory Human-Computer Interaction (HCI).

Aggression is a socially complex behaviour that intelligent virtual agents (IVAs) must convincingly convey in applications such as customer service and conflict training. Despite its importance, aggression remains understudied: prior work has focused on basic emotions and unimodal cues, providing little insight into how aggression can be modelled multimodally or systematically scaled by intensity. We present a psychologically grounded model that parametrises language, voice, body movement and facial expressions, across four aggression levels. We evaluated the model in two studies with 38 flight attendants. Experiment 1 tested unimodal cues, showing all modalities except language conveyed aggression gradients. Experiment 2 extended this by combining modalities, demonstrating that coordinated multimodal integration stabilised weaker language cues and produced perceptually robust aggression levels (low, mid, and high) with body and facial cues carrying most weight. Our work contributes the first validated multimodal, multi-level aggression model for IVAs, offering design principles for broader socially expressive agents.

Immersive virtual reality (VR) applications demand accurate, temporally coherent full-body pose tracking. Recent head-mounted camera-based approaches show promise in egocentric pose estimation, but encounter challenges when applied to VR head-mounted displays (HMDs), including temporal instability, inaccurate lower-body estimation, and the lack of real-time inference. To address these limitations, we present EgoPoseVR, an end-to-end framework for accurate egocentric full-body pose estimation in VR that integrates headset motion cues with egocentric RGB-D observations through a dual-modality fusion pipeline. A spatiotemporal encoder extracts frame- and joint-level representations, which are fused via cross-attention to fully exploit complementary motion cues across modalities. A kinematic optimization module then imposes constraints from HMD signals, enhancing the accuracy and stability of pose estimation. To facilitate training and evaluation, we introduce a large-scale synthetic dataset of over 1.8 million temporally aligned HMD and RGB-D frames across diverse VR scenarios. Experimental results show that EgoPoseVR outperforms state-of-the-art egocentric pose estimation models. A user study in real-world scenes further shows that EgoPoseVR achieved significantly higher subjective ratings in accuracy, stability, embodiment, and intention for future use compared to baseline methods. These results show that EgoPoseVR enables robust full-body pose tracking, offering a practical solution for accurate VR embodiment without requiring additional body-worn sensors or room-scale tracking systems.

Roboticists have long focused on areas far removed from everyday human work practices, raising questions about the usefulness of robots in various domains. An ethnographic study can help bridge this gap, but while there are some studies on human-robot interaction (HRI), many of them explore the relationship between ethnographic work and robot development without considering ethnographic reflexivity. This paper reports on a heterogeneous team involved in an elderly care project utilizing a pre-programmed social robot. Through a pragmatic inquiry lens, we iteratively improved the design of the robot systems as part of the research process. Our surprising findings reveal that the robot alone cannot fully support care work, and the design of the 'robotic' must extend beyond the robot itself and human-robot interaction. Instead, robot-assisted care work should focus on the design of the entire information technology system, of which the robot is only one component. This study highlights the need for real-life, user-centered, and pragmatic research, offering an exemplary account of how pragmatism can serve as a sensitizing framework for the HRI field.

Extensive research has been done in haptic feedback for texture simulation in virtual reality (VR). However, it is challenging to modify the perceived tactile texture of existing physical objects which usually serve as anchors for virtual objects in mixed reality (MR). In this article, we present ViboPneumo, a finger-worn haptic device that uses vibratory-pneumatic feedback to modulate (i.e., increase and decrease) the perceived roughness of the material surface contacted by the user's fingerpad while supporting the perceived sensation of other haptic properties (e.g., temperature or stickiness) in MR. Our device includes a silicone-based pneumatic actuator that can lift the user's fingerpad on the physical surface to reduce the contact area for roughness decreasing, and an on-finger vibrator for roughness increasing. The results of our perceptual study showed that the participants could perceive changes in roughness, both increasing and decreasing, compared to the original material surface. We also observed the overlapping roughness ratings among certain haptic stimuli (i.e., vibrotactile and pneumatic) and the originally perceived roughness of some materials without any haptic feedback. This suggests the potential to alter the perceived texture of one type of material to another in terms of roughness (e.g., modifying the perceived texture of ceramics as glass). Lastly, a user study of MR experience showed that ViboPneumo could significantly improve the MR user experience, particularly for visual-haptic matching, compared to the condition of a bare finger. We also demonstrated a few application scenarios for ViboPneumo.

Existing research showed that unpleasant haptic feedback, such as pain, could enhance the user experience and performance in various scenarios (e.g.entertainment and training).This paper introduces ThermOuch, a wearable thermo-haptic device that leverages the thermal grill illusion (TGI) to simulate pain sensations in virtual reality (VR) without causing actual invasive/non-invasive harm.Our results of the user-perception experiments revealed that higher temperature-changing rates, particularly with increased warming, were associated with more intense pain perceived by the participants through our system.Furthermore, a higher ratio of warm-to-cool temperature transitions reduced the sensation of coldness prior to pain.Our experiments also showed that introducing an additional stimulus unit potentially heightened pain perception, and altering the spacing between stimulus units modified the perceived pain area.Lastly, the user study in VR demonstrated that ThermOuch significantly enhanced the sense of presence and body ownership for the participants, as well as elevated their biosignal-indicated arousal levels.

There has been an increasing focus on haptic interfaces for virtual reality (VR), to support a high-quality touch experience. However, it is still challenging to haptically simulate the real-world walking experience in different fluid mediums. To tackle this problem, we present PropelWalker, a pair of calf-worn haptic devices for simulating the buoyancy and the resistant force when the human's lower limbs are interacting with different fluids and materials in VR. By using four ducted fans, two installed on each calf, the system can control the strength and the direction of the airflow in real time to provide different levels of force. Our technical evaluation shows that PropelWalker can generate vertical forces up to 27N in two directions (i.e., upward and downward) within 0.85 seconds. Furthermore, the system can stably maintain the generated force with minor turbulence. We further conducted three user-perception studies to understand the capability of PropelWalker to generate distinguishable force stimuli. First, we conducted the just-noticeable-difference (JND) experiments to investigate the threshold of the human perception of on-leg air-flow force feedback. Our second perception study showed that users could distinguish four PropelWalker-generated force levels for simulating different walking mediums (i.e., dry ground, water, mud, and sand), with an average accuracy of 94.2%. Lastly, our VR user study showed that PropelWalker could significantly improve the users' sense of presence in VR.

We present ThermAirGlove (TAGlove), a pneumatic glove which provides thermal feedback for users, to support the haptic experience of grabbing objects of different temperatures and materials in virtual reality (VR). The system consists of a glove with five inflatable airbags on the fingers and the palm, two temperature chambers (one hot and one cold), and the closed-loop pneumatic thermal control system. Our technical experiments showed that the highest temperature-changing speed of TAGlove system was 2.75°C/s for cooling, and the pneumatic-control mechanism could generate the thermal cues of different materials (e.g., foam, glass, copper, etc.). The user-perception experiments showed that the TAGlove system could provide five distinct levels of thermal sensation (ranging from very cool to very warm). The user-perception experiments also showed that the TAGlove could support users’ material identification among foam, glass, and copper with the average accuracy of 87.2%, with no significant difference compared to perceiving the real physical objects. The user studies on VR experience showed that using TAGlove in immersive VR could significantly improve users’ experience of presence compared to the situations without any temperature or material simulation.