This project brings together four investigators who identified an opportunity to bridge their disparate fields (gait analysis, body sensor networks, low power RF circuits, and gerontology) in order to address an extremely important health care problem of fall prevention. Their combined expertise addresses the following scientific objectives: (1) explore on-node signal processing and low power RF transceivers to balance energy consumption and mobility analysis fidelity in wireless on-body inertial sensing, (2) identify the minimal set of on-body sensor locations to provide high-quality mobility analysis, (3) determine the appropriate algorithms to identify fall prone individuals in controlled in- and out-of-lab data collections to assess the external influences of context and activities, and (4) validate the TEMPO-based data collection and processing algorithms in a naturalistic HFC living environment.
This project enables a new paradigm in elderly patient care to target fall prevention interventions to high fall risk individuals before fall incidents occur, preserving patient's health and quality of life while reducing health care costs. In addition, the above described fundamental scientific objectives apply in the broader application of energy efficient BSNs in a variety of application domains. The education and outreach plans focus on crossing the disciplinary divide between technology and health care, using hands-on public demonstrations, undergraduate laboratory modules, and multi-disciplinary videoconferencing graduate seminar courses to attract and develop leaders who can address the tremendous challenges that face the health care industry in the coming decades.
