Error-state Kalman filter for lower-limb kinematic estimation: Evaluation on a 3-body model

Michael V Potter; Stephen M Cain; Lauro V Ojeda; Reed D Gurchiek; Ryan S McGinnis; Noel C Perkins

doi:10.1371/journal.pone.0249577

Error-state Kalman filter for lower-limb kinematic estimation: Evaluation on a 3-body model

PLoS One. 2021 Apr 20;16(4):e0249577. doi: 10.1371/journal.pone.0249577. eCollection 2021.

Authors

Michael V Potter¹, Stephen M Cain¹, Lauro V Ojeda¹, Reed D Gurchiek², Ryan S McGinnis², Noel C Perkins¹

Affiliations

¹ Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, United States of America.
² M-Sense Research Group, University of Vermont, Burlington, VT, United States of America.

Abstract

Human lower-limb kinematic measurements are critical for many applications including gait analysis, enhancing athletic performance, reducing or monitoring injury risk, augmenting warfighter performance, and monitoring elderly fall risk, among others. We present a new method to estimate lower-limb kinematics using an error-state Kalman filter that utilizes an array of body-worn inertial measurement units (IMUs) and four kinematic constraints. We evaluate the method on a simplified 3-body model of the lower limbs (pelvis and two legs) during walking using data from simulation and experiment. Evaluation on this 3-body model permits direct evaluation of the ErKF method without several confounding error sources from human subjects (e.g., soft tissue artefacts and determination of anatomical frames). RMS differences for the three estimated hip joint angles all remain below 0.2 degrees compared to simulation and 1.4 degrees compared to experimental optical motion capture (MOCAP). RMS differences for stride length and step width remain within 1% and 4%, respectively compared to simulation and 7% and 5%, respectively compared to experiment (MOCAP). The results are particularly important because they foretell future success in advancing this approach to more complex models for human movement. In particular, our future work aims to extend this approach to a 7-body model of the human lower limbs composed of the pelvis, thighs, shanks, and feet.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Biomechanical Phenomena
Computer Simulation
Gait / physiology*
Humans
Lower Extremity / physiology*
Models, Biological*
Movement*
Range of Motion, Articular
Walking*

Grants and funding

Parts of this research were funded by US Army Contracting Command-APG, Natick Contracting Division, Natick, MA, contract number W911QY-15-C-0053 received by NCP. This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE 1256260 received by MVP. RDG and RSM receive funding for consulting with the University of Washington. RSM also receives funding from consulting for HX Innovations Inc. and Happy Health Inc. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors. The specific roles of these authors are articulated in the ‘author contributions’ section.