Model-Based Estimation of Ankle Joint Stiffness

Sensors (Basel). 2017 Mar 29;17(4):713. doi: 10.3390/s17040713.

Abstract

We address the estimation of biomechanical parameters with wearable measurement technologies. In particular, we focus on the estimation of sagittal plane ankle joint stiffness in dorsiflexion/plantar flexion. For this estimation, a novel nonlinear biomechanical model of the lower leg was formulated that is driven by electromyographic signals. The model incorporates a two-dimensional kinematic description in the sagittal plane for the calculation of muscle lever arms and torques. To reduce estimation errors due to model uncertainties, a filtering algorithm is necessary that employs segmental orientation sensor measurements. Because of the model's inherent nonlinearities and nonsmooth dynamics, a square-root cubature Kalman filter was developed. The performance of the novel estimation approach was evaluated in silico and in an experimental procedure. The experimental study was conducted with body-worn sensors and a test-bench that was specifically designed to obtain reference angle and torque measurements for a single joint. Results show that the filter is able to reconstruct joint angle positions, velocities and torque, as well as, joint stiffness during experimental test bench movements.

Keywords: BSN; body-worn sensors; joint stiffness estimation; magnetic, angular rate and gravity sensors.

MeSH terms

  • Ankle Joint*
  • Biomechanical Phenomena
  • Computer Simulation
  • Humans
  • Movement
  • Torque