Health management of older adults can be improved through convenient and objective assessment of their gait. Although a number of quantitative measures of walking, such as the variability of steps taken, have been shown to predict the risk of falls, these measurements are difficult to obtain outside the laboratory. It would be helpful to obtain accurate and objective measures in the clinic or even in the home during normal activities of daily living. Long-term monitoring could even be used to track compliance to a rehabilitation program or to determine when the dosage of medicines should be adjusted, all without requiring frequent visits to the clinic. Unfortunately, current devices for long-term monitoring are limited to simplistic data such as step count, and there is no convenient means to accurately measure the gait variables most indicative of mobility, balance, and fall risk. Miniature sensors are rapidly improving in accuracy and power economy, offering great potential for field-based activity assessment. Simple accelerometer-based devices have been miniaturized, and wireless systems can provide rough estimates of running speed and distance accurate enough for casual use, while remaining unobtrusive enough to wear conveniently for long durations. New microchip technologies make it feasible for highly accurate, inertial sensor systems to be packaged similarly for daily use. A major barrier for gait measurements is the need to eliminate drift errors that occur with these devices when estimating stride length and other quantities related to mobility. This project seeks to develop sensor fusion algorithms for this purpose, and integrate them with wearable inertial measurement sensors.
The Specific Aims of this project are to: 1. Implement drift reduction algorithms and software for integrating inertial sensor data to accurately estimate gait parameters. 2. Develop wireless sensor and receiver unit hardware for field-based gait monitoring, with miniature packages suitable for long-term use. 3. Perform accuracy and usability testing on younger and older adults, to characterize device specifications in realistic environments.
Falling and related injuries greatly limit mobility in older adults, and their risk can be reduced substantially with exercise, rehabilitation, and other interventions. It is currently difficult, however, to monitor mobility in the home and for long durations, either to assess compliance to an intervention or to determine dosage of medicine. This proposal seeks to develop new technology to enable accurate, long-term measurements of gait and mobility in the home.
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