%0 Conference Paper %1 abreu2016evaluating %A Abreu, João Gabriel %A Teixeira, João Marcelo Xavier Natário %A Figueiredo, Lucas Silva %A Teichrieb, Veronica %B 2016 XVIII Symposium on Virtual and Augmented Reality (SVR) %D 2016 %I IEEE %K brazilian-sign-language bsl gesture-recognition libras real sign-language sl support-vector-machine svm %P 64-70 %R 10.1109/SVR.2016.21 %T Evaluating Sign Language Recognition Using the Myo Armband %U https://ieeexplore.ieee.org/abstract/document/7517255 %X The successful recognition of sign language gestures by computer systems would greatly improve communications between the deaf and the hearers. This work evaluates the usage of electromyogram (EMG) data provided by the Myo armband as features for classification of 20 stationary letter gestures from the Brazilian Sign Language (LIBRAS) alphabet. The classification was performed by binary Support Vector Machines (SVMs), trained with a one-vs-all strategy. The results obtained show that it is possible to identify the gestures, but substantial limitations were found that would need to be tackled by further studies. %@ 978-1-5090-4149-7

@inproceedings{abreu2016evaluating, abstract = {The successful recognition of sign language gestures by computer systems would greatly improve communications between the deaf and the hearers. This work evaluates the usage of electromyogram (EMG) data provided by the Myo armband as features for classification of 20 stationary letter gestures from the Brazilian Sign Language (LIBRAS) alphabet. The classification was performed by binary Support Vector Machines (SVMs), trained with a one-vs-all strategy. The results obtained show that it is possible to identify the gestures, but substantial limitations were found that would need to be tackled by further studies.}, added-at = {2019-09-11T06:30:14.000+0200}, author = {Abreu, João Gabriel and Teixeira, João Marcelo Xavier Natário and Figueiredo, Lucas Silva and Teichrieb, Veronica}, biburl = {https://www.bibsonomy.org/bibtex/24ee04f36e2536e9b74d497d980ab1622/jpmor}, booktitle = {2016 XVIII Symposium on Virtual and Augmented Reality (SVR)}, crossref = {conf/svr/2016}, description = {Evaluating Sign Language Recognition Using the Myo Armband - IEEE Conference Publication}, doi = {10.1109/SVR.2016.21}, ee = {http://doi.ieeecomputersociety.org/10.1109/SVR.2016.21}, interhash = {754b2f5ebe14abddbbfcae715dbd61fa}, intrahash = {4ee04f36e2536e9b74d497d980ab1622}, isbn = {978-1-5090-4149-7}, keywords = {brazilian-sign-language bsl gesture-recognition libras real sign-language sl support-vector-machine svm}, month = {June}, pages = {64-70}, publisher = {IEEE}, school = {Universidade Federal de Pernambuco (UFPE)}, timestamp = {2020-10-07T13:36:50.000+0200}, title = {Evaluating Sign Language Recognition Using the Myo Armband}, url = {https://ieeexplore.ieee.org/abstract/document/7517255}, year = 2016 }