dc.contributor.author |
Sequeira, M. |
|
dc.contributor.author |
Naik, G.M. |
|
dc.contributor.author |
Parab, J.S. |
|
dc.contributor.author |
Gad, R.S. |
|
dc.date.accessioned |
2017-07-20T08:21:58Z |
|
dc.date.available |
2017-07-20T08:21:58Z |
|
dc.date.issued |
2017 |
|
dc.identifier.citation |
10. Nat. Symp. VLSI and Embedded System, 27-28 Apr 2017. Goa College of Engineering, Farmagudi, Goa. 2017; 4pp. |
en_US |
dc.identifier.uri |
http://irgu.unigoa.ac.in/drs/handle/unigoa/4853 |
|
dc.description.abstract |
The voiceless community of our society use sign language to communicate their views to the general public. Sign Language is basically making gestures by combining arm and hand movement along various orientations with facial expression to convey what they want to communicate. Since the general public do not have the knowledge of Sing Language it becomes difficult for the voiceless community to interface with general public. We have tried to bridge this communication gap for the Indian population by providing a system which gives voice to the voiceless community. We propose a system which converts the hand gestures performed by a person to text. The Signs will be from the Indian Sign Language and will correspond to each letter in the English alphabet. This system will be equipped with Inertial Measurement Unit(IMU) and the surface electromyography(sEMG) signal will be picked from the surface of the forehand in order to perform a sensor fusion of the data collected from the two different sources. The data collected will be fed to the classifier algorithm of Support Vector Machine(SVM).The detected Sign Language gesture will be displayed on a display as Text. |
en_US |
dc.subject |
Electronics |
en_US |
dc.title |
Sign Language Recognition using sEMG and IMU |
en_US |
dc.type |
Conference article |
en_US |