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DUB Group

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by T. Scott Saponas , Desney S. Tan , Dan Morris , Ravin Balakrishnan , Jim Turner , James A. L
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BibTeX

@MISC{Saponas_dubgroup,
    author = {T. Scott Saponas and Desney S. Tan and Dan Morris and Ravin Balakrishnan and Jim Turner and James A. L},
    title = {DUB Group},
    year = {}
}

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Abstract

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. ACM Classification: H.1.2 [User/Machine Systems]; H.5.2 [User Interfaces]: Input devices and strategies; B.4.2 [Input/Output

Citations

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2 Towards the Control of Individual Fingers of a Prosthetic Hand Using Surface EMG Signals - Tenore, Ramos, et al. - 2007
1 Inbar G.F. 2002. Classification of Finger Activation for Use in a Robotic Prosthesis Arm. Trans Neural Syst Rehabil Eng - Peleg, Braiman, et al.
1 Adechanische Auflau der kunstlichen Glieder - Schlesinger - 1919
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