AI & ML
Hugging Suit: Pneumatically-Actuated System Design for Remote Haptic Experiences
arXiv cs.HC0 views
arXiv:2610.08305v1 Announce Type: new Abstract: The COVID-19 pandemic emphasised the importance of remote emotional communication and highlighted a gap in existing technologies that lack haptic channels. While video calls maintain visual and auditory presence, they cannot convey the emotional depth of physical contact, especially hugging, a universally recognised form of intimacy and support. To explore this challenge, we developed the Hugging Suit, a pneumatically-actuated wearable system that enables users to simulate and receive remote hugs in real time. Unlike prior haptic systems that focus solely on tactile sensation, our approach integrates both technical and experiential considerations. The system integrates a programmable Air Actuator Matrix (AAM), a portable high-pressure pneumatic unit, and a fabric-based pressure sensor layer, enabling precise, wearable haptic feedback while remaining lightweight and mobile. Guided by a Research through Design (RtD) methodology, we iteratively refined the prototype to improve tactile resolution, overall usability, and user comfort, while introducing modular components to support flexible and scalable haptic configurations. In parallel, we explored how specific contextual factors, such as lighting, privacy, and the visibility of the remote partner, might shape the emotional and perceptual experience of receiving a remote hug. Preliminary feedback suggests that low-lit, private spaces, especially when users could also see their remote partner via video, improved emotional engagement and comfort during mediated haptic experiences. Our low-cost, maker-space-friendly approach contributes to affective haptics applications in long-distance relationships, emotional regulation, and remote therapeutic support.
Source:https://arxiv.org/abs/2610.08305PreviousBuilding A Civic Tool for Community-Police Engagement to Adapt Neighborhood PolicingNextLiving Dashboards: Automatically Self-Updating Visualization Dashboards
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