A group of young inventors in their 20s are helping those with hearing problems to give voice to their thoughts with automatic gesture-translation gloves.
Inspired by sign language interpreters in news and other programs, the group had an idea of enabling people with hearing impairments to "talk" as freely as anyone.
After conducting preliminary research on people with hearing impairment, students from Guangdong Polytechnic Normal University sought suggestions from their teachers and academicians at the Chinese Academy of Engineering.
A group of inventors in their 20s develop a kind of sign language translation glove, facilitating people who have hearing problems to communicate with others. [Photo by Wang Weixuan/Guangzhou Daily]
After several rounds of discussions and tests, a magic glove came into being. The glove uses flex sensors, contact sensors, and accelerometers to gather and record data from the motions of each hand and finger to differentiate meanings.
"Students from Ukraine once developed a similar kind of sign language translation glove in 2012," said Li Zhaohua, a spokesman for the group. "But their glove cannot clearly recognize the degree of flex in fingers and hands, or follow the motions in three dimensions."
"We provide a better solution, using smart controlling methods in algorithm," Li added. When the software is loaded into a cellphone it can identify the digital signals and translate them into voice for broadcast on the app.
Earlier this month, the sign language translation glove made its debut at the 2017 Thero International Innovation and Entrepreneurship Competition held in Guangzhou, Guangdong province, where it won a second prize.
Currently the glove can recognize about 500 sign gestures which are regularly used. Still in its initial version, the glove requires users to gesture properly in order to distinguish orientation and movements of the fingers, hands and arms.
"We are preparing to improve our product and develop a newly shaped glove," Li said. "It will be much easier to wear and better recognize the gesture patterns."