A new type of orthotic device is emerging from research underway at RIT. Dr. Edward Brown, assistant professor of electrical engineering and director of the Biomechatronic Learning Laboratory, is developing a platform that would allow orthotic devices to be controlled using physiological information, specifically electromyographic signals obtained from the surface of the skin (sEMG).
The platform is a robotic manipulator that has five degrees of freedom and resembles a human arm and is controlled using surface electromyographic signals. Currently, the team is studying pattern recognition and classification techniques to identify various features within the sEMG signal that can correlate with specific types of upper extremity motions. For example, if the platform receives a sEMG signal that recognizes the person is flexing his or her muscles, a control signal is sent to the robot to imitate the action.
Jay Radhakrishnan, a graduate electrical engineering student in the Biomechatronic Learning Laboratory, is using fuzzy logic to discriminate between different features in sEMG signals. Fuzzy logic is a soft computing technique that takes numerical data and translates it into linguistic terms that emulate how people think. Radhakrishnan hopes by applying fuzzy logic to sEMG signals he can create a more natural interaction between the user and the robot.
The ultimate goal is to create a rehabilitation exoskeleton system where the robotic device and the user can communicate seamlessly via physiological and biomechanical information. This type of orthotic device could aid people who suffer from muscular dystrophy or other conditions where the muscle is weakened or diseased, but the person's nervous system is still intact.
"We are very hopeful that this technology will lead to a new type of orthotic device," says Brown. "My greater vision is to expose students to STEM-related disciplines and perhaps inspire the next generation of rehabilitation roboticists and biomechatronic engineers."
The Biomechatronic Learning Laboratory was founded in 2007 by a grant from the National Science Foundation.