Indonesian Sign Language API (OpenSIBI API) as The Gateway Services for Myo Armband

Moh Zikky, Rizky Yuniar Hakkun, Buchori Rafsanjani


We create an API (Application Programming Interface) for Indonesian Sign Language (Sistem Isyarat Bahasa Indonesia/SIBI) which is called OpenSIBI. In this case study, we use the Myo Armband device to capture hand gesture data movement. It uses five sensors: Accelerometer, Gyroscope, Orientation, Orientation-Euler, and EMG. First, we record, convert and save those data into JSON dataset in the server as data learning. Then, every data request (trial data) from the client will compare them using k-NN Normalization process. OpenSIBI API works as the middleware which integrated to RabbitMQ as the queue request arranger. Every service request from the client will automatically spread to the server with the queue process. As the media observation, we create a client data request by SIBI Words and Alphabeth Game, which allows the user to answer several stages of puzzle-game with Indonesian Sign Language hand gesture. Game-player must use the Myo armband as an interactive device that reads the hand movement and its fingers for answering the questions given. Thus, the data will be classified and normalized by the k-NN algorithm, which will be processed on the server. In this process, data will pass OpenAPI SIBI (which connected to RabbitMQ) to queue every incoming data-request. So, the obtained data will be processed one by one and sent it back to the client as the answer.


SIBI API; Indonesian Sign Language; Myo Armband; Sign Language Dataset; OpenSIBI

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Angga Rahagiyanto, Achmad Basuki, Anwar Raditiya, Hand Gesture Classification for Sign Language Using Artificial Neural Network, 2017, Politeknik Elektronika Negeri Surabaya.

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International Journal of Artificial Intelligence & Robotics (IJAIR)
ISSN 2686-6269 (Online)
Published By Universitas Dr. Soetomo
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