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Sensing Tablet Grasp + Micro-mobility for Active Reading

on YouTube 19m
Talkat UIST 2015 · 2015-11-08..11-11· [developer-experience]

speakers

name:Dongwook Yoon
links:none on file
name:Ken Hinckley
links:none on file
name:Hrvoje Benko
links:none on file
name:Francois Guimbretire
links:none on file
name:Pourang Irani
links:none on file
name:Michel Pahud
links:none on file
name:Marcel Gavriliu
links:none on file

resources

video:https://youtu.be/sR0V97dKv4Y
slides:none on file

summary

Built a tablet prototype with a 44x26 capacitive array plus inertial sensors and a classifier that recognizes grips and motion; captures specific behaviors like top grasp, lateral swing handoff, bilateral side-edge holding, and thumb thumbing. Implements techniques: immersive zoom when holding sides, dog-ear bookmarking (tap to return), device passing with role-switching, and multi-device echoing for cross-referencing. Preliminary user study reports easy learning and robust recognition, though sideway passes sometimes miss and need more training data or deliberate nonrecognition.

AI-written summary · about

chapters (6)

  1. 0:00Start
  2. 2:28mobility Interactions
  3. 5:58Multi-hand Grasp
  4. 6:52ractions: Design space
  5. 9:14mark with 'Tip-to-Flip' Device
  6. 11:07sults and Design Insights

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