MyoSL: A framework for measuring usability of two-arm gestural electromyography for sign language
College
College of Computer Studies
Department/Unit
Software Technology
Document Type
Conference Proceeding
Source Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
10907 LNCS
First Page
146
Last Page
159
Publication Date
1-1-2018
Abstract
© Springer International Publishing AG, part of Springer Nature 2018. Several Sign Language (SL) systems have been developed using various technologies: Kinect, armbands, and gloves. Majority of these studies never considered user experience as part of their approach. With that, we propose a new framework that eases usability by employing two-arm gestural electromyography instead of typical vision-based systems see Fig. 5. Interactions can be considered seamless and natural with this way. In this preliminary study, we conducted focus group discussions and usability tests with signers. Based on the results of the usability tests, 90% of respondents found the armband comfortable. The respondents also stated that the armband was not intrusive when they tried to perform their sign gestures. At the same time, they found it aesthetically pleasing. Additionally, we produced an initial prototype from this experiment setup and tested them on several conversational scenarios. By using this approach, we enable an agile framework that caters the needs of the signer-user.
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Digitial Object Identifier (DOI)
10.1007/978-3-319-92049-8_11
Recommended Citation
Deja, J., Arceo, P., David, D., Gan, P., & Roque, R. (2018). MyoSL: A framework for measuring usability of two-arm gestural electromyography for sign language. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10907 LNCS, 146-159. https://doi.org/10.1007/978-3-319-92049-8_11
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