I.Q. Project Highlight: Lower Limb Orthotic Brace
ECE Associate Professor Yun Raymond Fu is researching a new approach to address the management of knee osteoarthritis, an important public health issue due to the high costs of treatment and the high number of affected. The Centers for Disease Control and Prevention says that nearly one in two people may develop this condition by the age of 85.
Professor Fu recognizes a technology gap in medicine with no low-cost, effective tools available to help address knee osteoarthritis.
Examining individualized remote rehabilitation is a key factor to improve mobility and reduce pain in patients. Professor Raymond Fu's answer involves an intelligent, articulated, and adjustable lower limb orthotic brace to manage the osteoarthritis.
Osteoarthritis is the most common form of arthritis in the knee. It is a degenerative, "wear-and-tear" type of arthritis that occurs most often in people 50 years of age and older, but may occur in younger people as well.
Professor Fu admits that rehabilitation can be effective for viewable human motion, it is largely unsuccessful in understanding underlying human neuro-muscular-skeletal and locomotion principles. In addition, it is challenging to capture fundamental underlying physical, physiological, and behavioral mechanisms. This forces professionals to use low-tech tools to help knee rehabilitation.
To address this, Professor Fu has developed a visual sensing and wearable magnetic sensing system to enable intelligent human-environment interaction capabilities by a synergistic combination of computer vision and robotics. The system uses an array of commercial-off-the-shelf computer-vision devices. These could easily be used in clinics, hospitals, or even at home.
Moving forward, Professor Fu and his research group are looking to abstract patient/device interactions into parametric and composable dynamic feature representations and facilitating development of individualized user models and exercise regimens.
This work is expected to advance research and training in behavioral mechanisms and cyber-physics, enhance automatic human action recognition, and provide new, more effective knee therapies.