The objective of this program is to provide a wearable instrument that monitors the level of the robustness of the multilevel control system responsible for human gait and balance stability. Long-term, free roaming gait dynamics measurements, recorded in either the clinic or during the unfettered subject's daily routine, will provide extended-time stride interval and length information necessary to perform fractal analysis of the individual's gait pattern history. Specifically, our system will record gait metric variations over large samples of successive steps. Fractal pattern analysis of the recorded data will provide incite into the organization and functioning of the relevant control systems. System design will focus upon the hardware precision and software accuracy design requirements for this necessary to unmask clinically relevant signs of existing or progressing gait and balance impairments.
Falls are a significant source of disability and death in the aging population. Also, poor performance in walking is associated with accelerated decline in physical function and elevated risk of admission to nursing home. As such, the dynamics of mobility during aging is an extremely important predictor of health and quality of life. We propose to develop and validate a system of hardware and analysis software to measure the likelihood of falling during free roaming activities from day to day. Evidence-based guidelines for interventions that have been shown to reduce risk of falls in older persons can then be employed.