Abstract
We introduce LowKeyEMG, a real-time human-computer interface that enables efficient text entry using only 7 gesture classes decoded from surface electromyo- graphy (sEMG). Prior work has attempted full-alphabet decoding from sEMG, but decoding large character sets remains unreliable, especially for individuals with motor impairments. Instead, LowKeyEMG reduces the English alphabet to 4 gesture keys, with 3 more for space and system interaction, to reliably translate simple one-handed gestures into text, leveraging the recurrent transformer-based language model RWKV for efficient computation. In real-time experiments, partic- ipants achieved average one-handed keyboardless typing speeds of 23.3 words per minute with LowKeyEMG, and improved gesture efficiency by 17% (relative to typed phrase length). When typing with only 7 keys, LowKeyEMG can achieve 99.2% top-3 word accuracy, demonstrating that this low-key typing paradigm can maintain practical communication rates. Our results have implications for assistive technologies and any interface where input bandwidth is constrained.
Authors
Lee, J. Y., Xiao, D., Kaasyap, S., Hadidi, N. R., Zhou, J. L., Cunningham, J., ... & Kao, J. C.
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