NSF Award
1721266
The broader impact/commercial potential of this project is in line with the grand challenge of developing teaching methods that optimize learning given the diversity of individual preferences and the complexity of each human brain. Because there is a great variability in stroke-induced lesions that result in marked differences in impairment and responsiveness to motor therapy, there is even a greater need to personalize motor training in post-stroke patients. The commercial impact of the personalized e-rehabilitation system, which will be developed and tested, derives from its value for patients, clinics, and insurers. For patients, the system will provide personalized training, and, because it will encapsulate research-based principles for effective and efficient neurorehabilitation of the upper extremity, it will largely improve patients' outcomes. For clinics, the system will increase revenues by increasing the number of visits per patient due to better outcomes and compliance, as well as the number of patients trained at once in clinic gyms. For insurers, the system will generate reports showing therapy effectiveness and, thus, validate reimbursements. <br/><br/>This Small Business Innovation Research (SBIR) Phase I project is improving functions of the upper extremities following neurological disorders that affect the motor system, in particular stroke, but also Parkinson's disease and traumatic brain injury. Because therapists treating patients with these disorders only have the time to deliver about a 1/10th of the necessary dose of motor training in the clinic, patients are requested to perform most of the training at home. A novel augmented reality training system will be developed and tested. The system will automatically deliver high doses of functional tasks via presentations of virtual targets or objects in the real world. Using state-of-the-art motion sensing technology, the system will accurately and precisely measure upper body movements, including hand opening and closing. Based on these measurements, it will maximize recovery by providing adaptive training. It will maximize patient engagement and motivation by providing real-time and summary feedback for task success and improvements.
