Abstract
Ambulatory estimation of gait and balance parameters requires knowledge of relative feet and centre of mass (CoM) positions. Inertial measurement units (IMU) placed on each foot, and on the pelvis are useful in tracking these segments over time, but cannot track the relative distances between these segments. Further, drift due to strapdown inertial navigation results in erroneous relative estimates of feet and CoM positions after a few steps. In this study, we track the relative distances using the assumptions of the Centroidal Moment Pivot (CMP) theory. An Extended Kalman filter approach was used to fuse information from different sources: strapdown inertial navigation, commonly used constraints such as zero velocity updates, and relative segment distances from the CMP assumption; to eventually track relative feet and CoM positions. These estimates were expressed in a reference frame defined by the heading of each step. The validity of this approach was tested on variable gait. The step lengths and step widths were estimated with an average absolute error of 4.6±1.5 cm and 3.8±1.5 cm respectively when compared against the reference VICON©. Additionally, we validated the relative distances of the feet and the CoM, and further, show that the approach proves useful in identifying asymmetric gait patterns. We conclude that a three IMU approach is feasible as a portable gait lab for ambulatory measurement of foot and CoM positions in daily life.
Highlights
G AIT kinematics and kinetics are necessary for assessing spatio-temporal as well as qualitative metrics such asBase of Support (BoS), and Margin of Stability (MoS), that are useful in assessing dynamic balance [1]
A few trials were removed from analysis due to issues with the reference setups
It was made sure that each subject had at least three walking trials per walking task
Summary
Base of Support (BoS), and Margin of Stability (MoS), that are useful in assessing dynamic balance [1]. Ambulatory assessment of these parameters helps us understand gait biomechanics outside the restricted laboratory environment, providing potential applications in daily life monitoring. Manuscript received April 8, 2020; revised July 13, 2020 and July 29, 2020; accepted August 4, 2020. Date of publication August 20, 2020; date of current version October 8, 2020. Buurke is with the Roessingh Research and Development, 7522 AH Enschede, The Netherlands, and with the Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
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