It is just a matter of time before people who sign could be heard and understood by people who do not have speech impairment, when the armband translator of Texas A&M University comes into full production.
Researchers at the Texas A&M University have developed an armband that can monitor arm muscle movements to translate sign language into text through sensors, which are later sent to a connected smartphone or computer. There are plenty of apps to help people speaking different languages communicate easily, a fact that does not apply to people who are deaf, mute or have disability speaking that requires them to use sign language. This device being created by the university will be of great help to people who sign and a great boost for people who do not know sign language, for it will facilitate communication between hearing and speech-impaired individuals and people without speech difficulties.
Sensors on the armband will monitor the movements of muscles as a person signs. The sensors will record the motion of the hand movements as well as the EMG (electromyography) signals that the wrist muscles produce while signing. An app then decodes the movements and translates them in written translation that could be viewed on a computer screen or a smartphone via Bluetooth.
The armband would be very beneficial for deaf people who sign as this alleviates the language barrier since not many people are able to understand sign language.
Testing and fine tuning
The technology, which is already in the testing stage still needs fine tuning. This will require the development of advanced algorithms so that the armband could accurately process and translate the various signals in real time. At the moment, according to Associate Professor of Biomedical Engineering at the university, Roozbeh Jafari, they decode the activities they capture from the wrist muscles, however, there are also some signals coming indirectly from the fingers if the wrist is still and the fingers are moving, in which case there is a difference in muscle activation.
To resolve the issue of the different ways of signing, the researchers have designed the system to have some level of accuracy when first used. It will eventually have the capability to adapt a learning model that will fit the user as the device is used over time, added Professor Jafari.
Looking into the future
The device does not look much at the moment although it is already working, albeit only decoding individual words. The research team of Texas A&M University hopes to make the device smaller to fit a user’s wrist like a wristwatch. They also plan to have the program decode complete sentences instead of single words. Included in their future plans is the incorporation of a synthetic voice speaker, which would potentially give voice to about 70 million deaf people worldwide.