Hand Grip Pressure Visualization for Task Assistance

Aman Sariya, Andrew Huard, Ishan Jain, Arthur Caetano, Tobias Höllerer, Misha Sra

Abstract: Tacit knowledge of hand grip force and pressure is essential for effective tool use and object manipulation. However, this information is challenging to communicate in virtual training scenarios. To address this, we introduce realtime hand grip pressure visualization that provides users with feedback on when to tighten or loosen their grip and which specific parts of the hand require adjustment. By offering task-specific visual pressure cues, users can learn and fine-tune their grasp for specific objects and tasks. Our pilot study tested three different visualization levels of detail and results indicate the medium level to outperform the low and high levels of detail.