Wearable sensors could one day
interpret the gestures in sign language and translate them into English,
providing a high-tech solution to communication problems between deaf people
and those who don’t understand sign language.
Engineers at Texas A&M University
are developing a wearable device that can sense movement and muscle
activity in a person's arms.
The device works by figuring out
the gestures a person is making by using two distinct sensors: one that
responds to the motion of the wrist and the other to the muscular movements in
the arm. A program then wirelessly receives this information and converts the
data into the English translation.
After some initial research, the
engineers found that there were devices that attempted to translate sign
language into text, but they were not as intricate in their designs.
"Most of the technology ...
was based on vision- or camera-based solutions," said study lead
researcher Roozbeh Jafari, an associate professor of biomedical engineering at
Texas A&M.
These existing designs, Jafari
said, are not sufficient because often when someone is talking with sign
language, they are using hand gestures combined with specific finger movements.
"I thought maybe we should
look into combining motion sensors and muscle activation," Jafari told
Live Science. "And the idea here was to build a wearable device."
The researchers built a prototype
system that can recognize words that people use most commonly in their daily
conversations. Jafari said that once the team starts expanding the program, the
engineers will include more words that are less frequently used, in order
to build up a more substantial vocabulary.One drawback of the prototype is
that the system has to be "trained" to respond to each individual
that wears the device, Jafari said. This training process involves asking the
user to essentially repeat or do each hand gesture a couple of times, which can
take up to 30 minutes to complete.
"If I'm wearing it and
you're wearing it — our bodies are different … our muscle structures are
different," Jafari said.
But, Jafari thinks the issue is
largely the result of time constraints the team faced in building the
prototype. It took two graduate students just two weeks to build the device, so
Jafari said he is confident that the device will become more advanced during
the next steps of development.
The researchers plan to reduce
the training time of the device, or even eliminate it altogether, so that the
wearable device responds automatically to the user. Jafari also wants to
improve the effectiveness of the system's sensors so that the device will be
more useful in real-life conversations. Currently, when a person gestures in
sign language, the device can only read words one at a time.
This, however, is not how people
speak. "When we're speaking, we put all the words in one sentence,"
Jafari said. "The transition from one word to another word is seamless and
it's actually immediate."
"We need to build
signal-processing techniques that would help us to identify and understand a
complete sentence," he added.
Jafari's ultimate vision is to
use new technology, such as the wearable sensor, to develop innovative user
interface between humans and computers.
For instance, people are already
comfortable with using keyboards to issue commands to electronic devices, but
Jafari thinks typing on devices like smart watches is not practical because
they tend to have small screens.
"We need to have a new user
interface (UI) and a UI modality that helps us to communicate with these
devices," he said. "Devices like [the wearable sensor] might help us
to get there. It might essentially be the right step in the right
direction."
Jafari presented this research at
the Institute of Electrical and Electronics Engineers (IEEE) 12th Annual Body
Sensor Networks Conference in June.

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