Credit: Texas A&M University
In Jafari’s system both inertial sensors and electromyographic sensors are placed on the right wrist of the user where they detect gestures and send information via Bluetooth to an external laptop that performs complex algorithms to interpret the sign and display the correct English word for the gesture. As Jafari continues to develop the technology, he says his team will look to incorporate all of these functions into one wearable device by combining the hardware and reducing the overall size of the required electronics. He envisions the device collecting the data produced from a gesture, interpreting it and then sending the corresponding English word to another person’s smart device so that he or she can understand what is being signed simply by reading the screen of their own device. In addition, he is working to increase the number of signs recognized by the system and expanding the system to both hands.
“The combination of muscle activation detection with motion sensors is a new and exciting way of understanding human intent with other applications in addition to enhanced SLR systems, such as home device activations using context-aware wearables,” Jafari says.
Jafari is associate professor in Texas A&M’s Department of Biomedical Engineering, associate professor in the Department of Computer Science and Engineering and the Department of Electrical and Computer Engineering, and researcher at Texas A&M Engineering Experiment Station’s Center for Remote Health Technologies and Systems. His research focuses on wearable computer design and signal processing. He is director of the Embedded Signal Processing Laboratory (http://jafari.tamu.edu/).
About the Center for Remote Health Technologies and Systems (CRHTS)
The Center for Remote Health Technologies and Systems is designing and developing advanced health technologies and systems to enable healthy living through health monitoring and disease diagnosis, management and prevention. The center’s mission is to identify and overcome the unmet needs of patients and health care providers through the development of breakthrough remote health care devices, biosignal mapping algorithms, remote health analytics and information systems that will improve access, enhance quality, and reduce the cost of health care.
About the Texas A&M Engineering Experiment Station (TEES)
As an engineering research agency of Texas, TEES performs quality research driven by world problems; strengthens and expands the state’s workforce through educational partnerships and training; and develops and transfers technology to industry. TEES partners with academic institutions, governmental agencies, industries and communities to solve problems to help improve the quality of life, promote economic development and enhance educational systems. TEES, a member of the Texas A&M University System is in its 100th year of engineering solutions.