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Jonathan Isaac Segal

Publications and source records attributed to Jonathan Isaac Segal.

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Alignment Under Pressure: AR-HMD Support Tools for Action Teams

Team communication breakdowns represent a contributor to patient safety risks within action teams-defined as interdependent groups of specialized people who perform coordinated work under high workload, time pressure, and uncertainty. Approximately 70% of such instances lead to adverse patient outcomes amid intense time pressure, uncertainty, and high cognitive load. While prior research has focused on maintaining shared cognition during these interactions, existing technologies largely prioritize individual task execution and decision-making, offering limited support for real-time team coordination. This study investigates the potential of augmented reality head-mounted displays (AR-HMDs) to address this gap by facilitating what we call 'team alignment' - the active maintenance of shared understanding regarding tasks, patient state, responsibilities, and ongoing clinical activity. Through an 11-month multi-phase qualitative study with ten healthcare professionals, we first elicited coordination challenges through semi-structured interviews complemented by real-time storyboard creation. Participants then engaged in reflection and refinement of these scenarios while contemplating the potential impact of AR-HMDs on their situation. Our findings revealed that breakdowns frequently arose when clinicians lacked sufficient contextual information, when assigned responsibilities did not align with available expertise, or when procedural progress was difficult to track - particularly during critical bedside activity. We subsequently developed the Team Alignment and Coordination Taxonomy (TACT), encompassing information, expertise, procedural, and cognitive dimensions. By reframing coordination as this active maintenance of alignment, our research shifts the design focus from individual decision support systems to holistic, team-level system interventions.

cs.HC

Accessible Nonverbal Cues to Support Conversations in VR for Blind and Low Vision People

Social VR has increased in popularity due to its affordances for rich, embodied, and nonverbal communication. However, nonverbal communication remains inaccessible for blind and low vision people in social VR. We designed accessible cues with audio and haptics to represent three nonverbal behaviors: eye contact, head shaking, and head nodding. We evaluated these cues in real-time conversation tasks where 16 blind and low vision participants conversed with two other users in VR. We found that the cues were effective in supporting conversations in VR. Participants had statistically significantly higher scores for accuracy and confidence in detecting attention during conversations with the cues than without. We also found that participants had a range of preferences and uses for the cues, such as learning social norms. We present design implications for handling additional cues in the future, such as the challenges of incorporating AI. Through this work, we take a step towards making interpersonal embodied interactions in VR fully accessible for blind and low vision people.

cs.HC