Toward Kinematics-and Kinetics-Based Predictions of Muscle Activity in Dynamic Sitting

• Author / Creator

  Roberts, Brad W. R.

• Recent work suggests that closed-loop electrical stimulation may restore dynamic trunk stability following neuromuscular impairment. However, developing such neuroprostheses requires quantitative predictions of the activation profiles of relevant muscles under different types of dynamic trunk disturbances experienced in daily life during non-impaired sitting. The types of disturbances that may be experienced include intrinsic instability or external displacement of the support surface, as well as the exposure to external trunk forces. Muscle activity predictions could be based on characteristic angular kinematics (i.e., the kinematics characterizing trunk stabilization) or the body’s center of pressure (CoP) displacement in these dynamic sitting paradigms. Several challenges exist, however, that need to be resolved to allow kinematics- or kinetics-based predictions of muscle activity to be obtained in dynamic sitting. First, the kinematics characterizing trunk stabilization in unstable sitting as well as the relation between kinematics and the muscle activity in this paradigm are unknown. Second, while the body’s CoP displacement in dynamic sitting can be measured by instrumenting the support surface with a force plate, in perturbing the support surface, the acquired kinetic data will contain artifacts due to acceleration of the platform. Existing methods for removing these so-called force plate inertial components (FPIC) require knowledge of the inertial properties of the platform. The objectives of this thesis research were therefore to (1): quantify the kinematics characterizing trunk stabilization in unstable sitting; (2) quantify both the spatial and temporal relations between the characteristic kinematics and the muscle activity in unstable sitting; and (3) propose and validate a method for estimating the inertial properties and FPIC for any instrumented platform. Using an unstable sitting paradigm, the angular motion of the base of support (BoS), pelvis, and trunk as well as bilateral electromyograms from fourteen trunk and upper leg muscles were recorded in fifteen non-disabled participants. To characterize the kinematics in unstable sitting, the angular motion of the BoS, pelvis, and trunk were quantified and compared. The trunk was stabilized through relatively large BoS motion, with the trunk adopting a quasi-static pose. Based on these insights, the relationship between BoS angular displacement and the electromyograms was quantified using cross-correlation analysis. During unstable sitting, the trunk was stabilized through direction-specific activation of the trunk and upper leg muscles that preceded BoS displacement temporally. The proposed method for estimating the inertial properties and FPIC for any instrumented platform was validated exemplarily by estimating the inertial properties specifically for the Computer-Assisted Rehabilitation Environment (CAREN). Unloaded ramp-and-hold perturbations (for estimation) and unloaded random perturbations (for validation) were executed to obtain the force, moment, and motion of the CAREN platform. Inertial properties were estimated by minimizing the error between the measured and computed inertial forces and moments. Obtained estimates were validated by comparing the measured and computed forces and moments when keeping the inertial properties fixed. The estimates of the CAREN’s inertial properties exhibited low variability across trials, with excellent agreement between the measured and computed forces and moments for the validation trials. Future work will use the obtained relation between BoS motion and trunk and upper leg muscle activity during unstable sitting to predict the kinematics-based muscle activation patterns within a closed-loop electrical stimulation system for dynamic sitting. Future work will also use the developed method for estimating the inertial properties and FPIC for any instrumented platform to obtain reliable estimates of the kinetic data used in analyses that quantify the relation between the body’s CoP displacement and the muscle activity in dynamic sitting. Relations obtained from such analyses can again be used to predict the CoP-based muscle activation patterns within a closed-loop electrical stimulation system for dynamic sitting.

• Subjects / Keywords

  • Posturographic measures
  • Cross-correlation function
  • Kinetics
  • Unstable sitting
  • Dynamic sitting
  • Kinematics
  • Muscle activity
  • Instrumented platform

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-qhp3-st94

• License

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