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UIST
2009
ACM

Enabling always-available input with muscle-computer interfaces

14 years 29 days ago
Enabling always-available input with muscle-computer interfaces
Previous work has demonstrated the viability of applying offline analysis to interpret forearm electromyography (EMG) and classify finger gestures on a physical surface. We extend those results to bring us closer to using musclecomputer interfaces for always-available input in real-world applications. We leverage existing taxonomies of natural human grips to develop a gesture set covering interaction in free space even when hands are busy with other objects. We present a system that classifies these gestures in real-time and we introduce a bi-manual paradigm that enables use in interactive systems. We report experimental results demonstrating four-finger classification accuracies averaging 79% for pinching, 85% while holding a travel mug, and 88% when carrying a weighted bag. We further show generalizability across different arm postures and explore the tradeoffs of providing real-time visual feedback.
T. Scott Saponas, Desney S. Tan, Dan Morris, Ravin
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where UIST
Authors T. Scott Saponas, Desney S. Tan, Dan Morris, Ravin Balakrishnan, Jim Turner, James A. Landay
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