Older adults face ergonomic barriers in virtual reality (VR), particularly with head-mounted displays (HMDs), which are heavy and poorly suited for fragile musculoskeletal systems. This poster introduces a 3D-printed support system that alleviates the weight of the headset by redistributing it to an external frame. This solution promotes accessibility by allowing passive, seated VR experiences, enabling better comfort and extending the use of VR for seniors in health, leisure, and telepresence contexts.

Participants of one-to-many videoconferencing calls often experience a significant loss of affective feedback due to the limitations of the medium. To address this problem, we present Co-Here: a videoconferencing module that renders participant-driven animations that convey group affect without relying on categorical emotion detection or signaling. Co-Here consolidates and visualizes facial expressions and head movements of fellow videoconferencers, providing a sufficient medium for others to meaningfully construct emotional impressions. Our qualitative user study showed that the system helped users feel a sense of alignment with the emotions of others using the system. Co-Here had the most utility to presentation viewers, who reported that the system offered a low-attention alternative to gauging the sentiment of the crowd.

Our perception of emotion is highly contextual. Changes in the environment can affect our narrative framing, and thus augment our emotional perception of interlocutors. User environments are typically heavily suppressed due to the technical limitations of commercial videoconferencing platforms. As a result, there is often a lack of contextual awareness while participating in a video call, and this affects how we perceive the emotions of conversants. We present a videoconferencing module that visualizes the user's aural environment to enhance awareness between interlocutors. The system visualizes environmental sound based on its semantic and acoustic properties. We found that our visualization system was about 50% effective at eliciting emotional perceptions in users that was similar to the response elicited by environmental sound it replaced.The contributed system provides a unique approach to facilitate ambient awareness on an implicit emotional level in situations where multimodal environmental context is suppressed.

Modeling with multimodal data in the wild poses similar challenges in human-computer and human-robot interaction (HCI, HRI). This workshop series thus blends HCI and HRI to jointly address a broad range of current topics in multimodal modeling aimed at designing intelligent systems in the wild. From addressing data scarcity in multimodal user state recognition to emotion prediction from EEG while listening to music, our third workshop in this series aims to further stimulate this important multidisciplinary exchange.

Today's smartphone notification systems are incapable of determining whether a notification has been successfully perceived without explicit interaction from the user. If the system incorrectly assumes that a notification has not been perceived, it may repeat it redundantly, disrupting the user and others (e.g., phone ringing). Or, if it incorrectly assumes that a notification was perceived, and therefore fails to repeat it, the notification will be missed altogether (e.g., text message). Results from a laboratory study confirm, for the first time, that both vibrotactile and auditory smartphone notifications induce skin conductance responses (SCR), that the induced responses differ from that of arbitrary stimuli, and that they could be employed to predict perception of smartphone notifications after their presentation using wearable sensors.

Our smartphones are constantly fighting to capture our attention, oftentimes causing significant disruption in professional and social contexts. In contrast with prior smart notification systems work focused on external contextual information (e.g., environment, user activity, etc.), my research explores how the notification experience could be enhanced by providing smartphones with a better awareness of their user's psycho-physiological state both prior to, but more importantly immediately after the presentation of alerts. This paper first summarizes findings from the evaluation of a novel notification perception classification technique based on wearable physiological sensing, and a non-intrusive mobile journaling mechanisms adapted to modern smartphone usage. From there, a tentative sequence of studies is presented, aiming to answer the project's remaining research questions.

Experience Sampling Methods (ESM) allow the timely collection of subjective self-reports that would otherwise be impossible to measure accurately in ecologically valid scenarios. Recent work suggests that unlock journaling allowed the collection of more data points per day, was faster and perceived as being less intrusive by participants than notification-based ESM. This work extends the unlock journaling field by introducing a novel lockscreen data collection mechanism harnessing an increasingly popular authentication mechanism: the fingerprint sensor. Results collected during a twelve-day user study with fingerprint sensor users show that fingerprint sensor gesture reporting compares favorably to Slide-to-X approaches. The proposed gestural interface was subjectively perceived as being the fastest, least intrusive, and overall most preferred interface, in addition to offering the highest response compliance. By offering a reporting mechanism better aligned with modern smartphone unlocking habits, this work encourages the deployment of unlock journaling in the wild.

Operating power tools over extended periods of time can pose significant risks to humans, due to the strong forces and vibrations they impart to the limbs. Telemanipulation systems can be employed to minimize these risks, but may impede effective task performance due to the reduced sensory cues they typically convey. To address this shortcoming, we explore the benefits of augmenting these cues with the addition of audition, vibration, and force feedback, and evaluate them on users' performance in a VR mechanical assembly task employing a simulated impact wrench. Our research focuses on the utility of vibrotactile feedback, rendered as a simplified and attenuated version of the vibrations experienced while operating an actual impact wrench. We investigate whether such feedback can serve to enhance the operator's awareness of the state of the tool, as well as a proxy for the forces experienced during collisions and coupling, while operating the tool an actual impact wrench. Results from our user study comparing feedback modalities confirm that the introduction of vibrotactile, in addition to auditory feedback can significantly improve user performance as assessed by completion time. However, the addition of force feedback to these two modalities did not further improve performance.

Considerable effort has been invested in the development of effective emotion and behavior recognition techniques. In comparison, little work has been devoted to technologies that can be used to induce specific emotional and behavioral responses, with most such research relying on the presentation of video or images. In this article, we propose a novel technique for the elicitation of emotion based on audio-tactile stimulation. Taking advantage of the relationship between tickling, laughter and emotional states, we conducted an experiment to map the perception of the tickle sensation as a function of vibrotactile stimulation frequency, quantify the effect of hearing laughter stimulus on the perceived intensity of the tactile experience, and assess the potential of the proposed multimodal approach to induce observable mirthful responses. Experimental evidence shows that the perceived intensity of the auditory laughter stimulus has a repeatable scaling effect on the tickle sensation and that the proposed audio-tactile stimulation is a promising approach to laughter elicitation. These findings may inform the design of future multimodal affective interfaces by allowing a more informed prediction of induced emotional and behavioral responses.