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

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 fra

SUBMITTER: Potter MV 

PROVIDER: S-EPMC8057618 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature