American Sign Language Electromiographic Alphabet Sign Translator

Edgar Armando Catalan-Salgado, Cristhian Lopez-Ramirez, Roberto Zagal-Flores

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationTelematics and Computing - 8th International Congress, WITCOM 2019, Proceedings
EditorsMiguel Felix Mata-Rivera, Roberto Zagal-Flores, Cristian Barría-Huidobro
PublisherSpringer
Pages162-170
Number of pages9
ISBN (Print)9783030332280
DOIs
StatePublished - 2019
Event8th International Congress on Telematics and Computing, WITCOM 2019 - Merida, Mexico
Duration: 4 Nov 20198 Nov 2019

Publication series

NameCommunications in Computer and Information Science
Volume1053 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th International Congress on Telematics and Computing, WITCOM 2019
Country/TerritoryMexico
CityMerida
Period4/11/198/11/19

Keywords

  • American Sign Language
  • Artificial intelligence and health
  • KNN
  • Pattern recognition

Fingerprint

Dive into the research topics of 'American Sign Language Electromiographic Alphabet Sign Translator'. Together they form a unique fingerprint.

Cite this