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- W2097497903 abstract "There has been recent interest in designing systems that use the tongue as an input interface. Prior work however either require surgical procedures or in-mouth sensor placements. In this paper, we introduce TongueSee, a non-intrusive tongue machine interface that can recognize a rich set of tongue gestures using electromyography (EMG) signals from the surface of the skin. We demonstrate the feasibility and robustness of TongueSee with experimental studies to classify six tongue gestures across eight participants. TongueSee achieves a classification accuracy of 94.17% and a false positive probability of 0.000358 per second using three-protrusion preamble design." @default.
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- W2097497903 date "2014-04-26" @default.
- W2097497903 modified "2023-10-13" @default.
- W2097497903 title "Non-intrusive tongue machine interface" @default.
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- W2097497903 doi "https://doi.org/10.1145/2556288.2556981" @default.
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