DexteriSync

Skin temperature is an important physiological factor for human hand dexterity. Leveraging this feature, we engineered an exoskeleton, called DexteriSync, that can dynamically adjust the user's finger dexterity and induce different thermal perceptions by modulating finger skin temperature.

This exoskeleton comprises flexible silicone-copper tube segments, 3D-printed finger sockets, a 3D-printed palm base, a pump system, and a water temperature control with a storage unit. It comprises two heat transfer methods, copper material conduction and water cooling convection, to modulate the user's finger temperature dynamically. By monitoring the water temperature and wearing time, DexteriSync changes a user’s finger dexterity and thermal perception while transmitting haptic feedback.

By realising an embodied experience of compromised dexterity, DexteriSync can help product designers understand the lived experience of compromised hand dexterity, such as that of the elderly and/or neurodivergent users, when designing daily necessities for them. We validated DexteriSync via a technical evaluation and two user studies, demonstrating that it can change skin temperature, dexterity, and thermal perception.

An exploratory session with design students and an autistic compromised dexterity individual, demonstrated the exoskeleton provided a more realistic experience compared to video education, and allowed them to gain higher confidence in their designs. The results advocated for the efficacy of experiencing embodied compromised finger dexterity, which can promote an understanding of the related physical challenges and lead to a more persuasive design for assistive tools.

Ximing Shen, Youichi Kamiyama, Kouta Minamizawa, and Jun Nishida. 2024. DexteriSync: A Hand Thermal I/O Exoskeleton for Morphing Finger Dexterity Experience. In The 37th Annual ACM Symposium on User Interface Software and Technology (UIST ’24), October 13–16, 2024, Pittsburgh, PA, USA. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3654777.3676422

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Magnus | SIGGRAPH2024