Smart Shoe for Balance, Fall Risk Assessment and Applications in Wireless Health

A new system combining embedded networked sensing, signal processing, and state detection algorithms have been developed to create a smart shoe for individuals who are prone to falls. This system monitors walking behaviors and uses a fall risk estimation model to predict the future risk of a fall. The model incorporates variability and correlation of features extracted from walking behavior, which have been identified by geriatric motion study experts as precursors to balance abnormality and fall risk. This system provides an affordable, mobile balance abnormality detection system, which is reliable, easily customizable for individual users, context aware which can be guided by experts. This system demonstrates capabilities that meet those of dedicated gait measurement laboratories, but at a much reduced cost, with greater user convenience and with detection capability in the user environment. In addition, this smart shoe system comprises a platform that we wish to share for diverse application domains, including urban and participatory sensing, behavior analysis, and novel applications that incorporate social networking