TY  - CONF
ID  - SisLab4748
UR  - http://dx.doi.org/10.1109/ISMEE54273.2021.9774139
A1  - Nhu, Chi Tran
A1  - Dang, Phu Nguyen
A1  - Thanh, Van Nguyen Thi
A1  - Thuy, Ha Tran Thi
A1  - Thanh, Van Dau
A1  - Thanh, Tung Bui
Y1  - 2021///
N2  - In this report, we develop a system converting sign language into voices and text. The system includes a glove attached self-developed ionic liquid-based strain sensors on each finger to detect the movement of them. When the hand move to express a letter lead to the resistance of the strain sensors on each finger change. Therefore, through the information from set of sensors, the system can recognize the letter that user want to convey. A measuring and data acquisition circuit also are developed to receive and analyze data from the sensors. Furthermore, a data digitizing method is proposed as a solution for decoding purpose. The system is tested with 10 distinguished basic letters in American Sign Language table (ASL). The results show the accuracy of system is 98%. The system operates stably with the low power of 0.81W at rest state and 1.71W when working. Besides, applications on smartphone and PC are also built to translate the data into text and speech. These apps make it easier to communicate with deaf people. With achieved results, the system is fully extensible to detect more letters in ALS table in the future
TI  - A Sign Language Recognition System Using Ionic Liquid Strain Sensor
SP  - 263
AV  - public
EP  - 267
T2  - 2021 3rd International Symposium on Material and Electrical Engineering Conference (ISMEE)
ER  -