Article

Gait parameters such as stride length, width, and period, as well as their
respective variabilities, are widely used as indicators of mobility and walking
function. Foot placement and its variability have thus been applied in areas such
as aging, fall risk, spinal cord injury, diabetic neuropathy, and neurological
conditions. But a drawback is that these measures are presently best obtained
with specialized laboratory equipment such as motion capture systems and
instrumented walkways, which may not be available in many clinics and certainly
not during daily activities. One alternative is to fix inertial measurement units
(IMUs) to the feet or body to gather motion data. However, few existing methods
measure foot placement directly, due to drift associated with inertial data. We
developed a method to measure stride-to-stride foot placement in unconstrained
environments, and tested whether it can accurately quantify gait parameters over
long walking distances. The method uses ground contact conditions to correct for
drift, and state estimation algorithms to improve estimation of angular
orientation. We tested the method with healthy adults walking over-ground,
averaging 93 steps per trial, using a mobile motion capture system to provide
reference data. We found IMU estimates of mean stride length and duration within
1% of motion capture, and standard deviations of length and width within 4% of
motion capture. Step width cannot be directly estimated by IMUs, although lateral
stride variability can. Inertial sensors measure walks over arbitrary distances,
yielding estimates with good statistical confidence. Gait can thus be measured in
a variety of environments, and even applied to long-term monitoring of everyday
walking.
CI - Copyright (c) 2013. Published by Elsevier B.V.

Langue : ANGLAIS