Development of an Intelligent Robotic System for Neural Rehabilitation
Over twenty-six million people worldwide (a few millions in US alone) are suffering from walking disabilities caused by traumatic injuries, brain and spinal cord diseases, or other health problems. Healthcare research has shown that many of them can resume their walking capabilities by performing repetitive activities and exercises of their legs with the assistance of rehabilitation professionals and equipment. The conventional methods for leg rehabilitation require two to four healthcare professionals (e.g., therapists, nurses, and training technicians, etc.) working with a patient on a special device like a treadmill. It is a very labor-intensive and costly process. With the advance of robotics and automation technologies, robotics-assisted devices for limb rehabilitation are being developed across the world. However, the products available so far can still perform very simple mechanical assistance to the patients. There is a great need of applying intelligent robotics technology to make neural rehabilitation more smartly and efficiently. The goal of this research is to develop advanced technology for robotics-assisted neural rehabilitation. More specifically, the project is to develop and investigate a cable-robot based active body suspension system which is smart and user-friendly in the sense that it can cognitively coordinates both doctor.s objectives and patient.s physical reactions to achieve optimal neural rehabilitation. The technology, if eventually developed successfully, will significantly improve the effectiveness and efficiency of neurological rehabilitation. In addition, the system can also be extended to the applications of training astronauts for walking in microgravity environment and training athletes for achieving optimal performance. This short-term IRG project will focus on preliminary-level concept development and study of the new system. The project will be carried out by a team of three faculty members, a Ph.D. student, and a master student. The three PI.s are from three different departments and two different colleges. They will be complementing each other. The team will also collaborate with a group of researchers at UTEP.
