Abstract
Communication between people is complicated, thus is due to correct idea and thought expression. But for the deaf or mute people this is even worse due to that our main communication channel is sound. They can use their own language using sign and ideograms made with hands, called American Sign Language. But as every language it is needed to learn and the population that dominate this language is small. In this work we propose an American Sign Language translator for 24 alphabet signs, using a wearable that give us eight electromiographic signals and KNN classifier for signs processing with 80% of accuracy.
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Acknowledgments
The authors are grateful to Instituto Politecnico Nacional for the economic support given to the research project number 20196065 given through the Secretaria de investigacion y posgrado.
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Catalan-Salgado, EA., Lopez-Ramirez, C., Zagal-Flores, R. (2019). American Sign Language Electromiographic Alphabet Sign Translator. In: Mata-Rivera, M., Zagal-Flores, R., Barría-Huidobro, C. (eds) Telematics and Computing. WITCOM 2019. Communications in Computer and Information Science, vol 1053. Springer, Cham. https://doi.org/10.1007/978-3-030-33229-7_14
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DOI: https://doi.org/10.1007/978-3-030-33229-7_14
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