The broader impact/commercial potential of this I-Corps project is to predict and avert falls and fall-related injuries/deaths of older adults with high risks of fall due to various age-related chronic diseases such as diabetes, Alzheimer's disease, and other dementias, Parkinson's disease and heart failure. Falls are a leading cause of unintentional injuries and seventh leading cause of mortality among older people aged 65 and over, which leads to approximately 3 million emergency department visits per year in U.S. alone. Prevention of falls will not only improve the overall health outcomes and save lives, but also will benefit society by reducing the expenses in medical treatment and emergency department visits. Specifically, the successful commercialization of the proposed technology could provide value to all senior care stakeholders such as hospitals, caregivers including long-term care facilities and family members, government and private insurers and age-related academic institutions and assisted device manufacturers.
This I-Corps project will further develop an artificial compound eye camera (ACECam) system that can extract clinically-relevant gait and mobility data, such as gait speed and sit-to-stand time, from the daily life of older adults who can have higher risk of falls. By integration of innovative compound eye optics with off-the-shelf image sensors, the ACECam technology can significantly reduce the computational costs of motion tracking and action recognition with the algorithms for clinical-relevant gait and mobility data developed based on convolutional neural network. Additionally, ACECam is unobtrusive for the daily life of older adults by not requiring wearable sensor systems that are commonly applied in current gait/motion tracking wearables. The raw data acquired by ACECam contains limited visual information and so will protect visual privacy of the users.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
