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

Links

Abstract

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.

Cited Works (18)

Year	Entry
2002	Wu G, Siegler S, Allard P, Kirtley C, Leardini A, Rosenbaum D, Whittle M, D'Lima DD, Cristofolini L, Witte H, Schmid O, Stokes I. ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion, I: ankle, hip, and spine. J Biomech. 2002;35(4):543-548.
2005	Hof AL, Gazendam MGJ, Sinke WE. The condition for dynamic stability. J Biomech. January 2005;38(1):1-8.
1990	Winters JM, Woo SL-Y, eds. Multiple Muscle Systems: Biomechanics and Movement Organization. New York, NY: Springer-Verlag; 1990.
2005	Wu G, van der Helm FCT, Veeger HEJ, Makhsous M, Van Roy P, Anglin C, Nagels J, Karduna AR, McQuade K, Wang X, Werner FW, Buchholz B. ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion, II: shoulder, elbow, wrist and hand. J Biomech. May 2005;38(5):981-992.
1995	Cappozzo A, Catani F, Della Croce U, Leardini A. Position and orientation in space of bones during movement: anatomical frame definition and determination. Clin Biomech (Bristol, Avon). June 1995;10(4):171-178.
1993	Cole GK, Nigg BM, Ronsky JL, Yeadon MR. Application of the joint coordinate system to three-dimensional joint attitude and movement representation: a standardization proposal. J Biomech Eng. November 1993;115(4A):344-349.
1999	Cholewicki J, Juluru K, Radebold A, Panjabi MM, McGill SM. Lumbar spine stability can be augmented with an abdominal belt and/or increased intra-abdominal pressure. Eur Spine J. October 1999;8(5):388-395.
2006	Kang HG, Dingwell JB. A direct comparison of local dynamic stability during unperturbed standing and walking. Exp Brain Res. June 2006;172(1):35-48.
1996	Cholewicki J, McGill SM. Mechanical stability of the in vivo lumbar spine: implications for injury and chronic low back pain. Clin Biomech (Bristol, Avon). January 1996;11(1):1-15.
2005	Cappozzo A, Della Croce U, Leardini A, Chiari L. Human movement analysis using stereophotogrammetry, I: theoretical background. Gait Post. February 2005;21(2):186-196.
1985	Huiskes R, Kremers J, de Lange A, Woltring HJ, Selvik G, van Rens TJG. Analytical stereophotogrammetric determination of three-dimensional knee-joint geometry. J Biomech. 1985;18(8):559-570.
2005	Leardini A, Chiari L, Della Croce U, Cappozzo A. Human movement analysis using stereophotogrammetry, III: soft tissue artifact assessment and compensation. Gait Post. February 2005;21(2):212-225.
2005	Chiari L, Della Croce U, Leardini A, Cappozzo A. Human movement analysis using stereophotogrammetry, II: instrumental errors. Gait Post. February 2005;21(2):197-211.
1990	Kadaba MP, Ramakrishnan HK, Wootten ME. Measurement of lower extremity kinematics during level walking. J Orthop Res. May 1990;8(3):383-392.
2005	Della Croce U, Leardini A, Chiari L, Cappozzo A. Human movement analysis using stereophotogrammetry, IV: assessment of anatomical landmark misplacement and its effects on joint kinematics. Gait Post. February 2005;21(2):226-237.
1996	Prieto TE, Myklebust JB, Hoffmann RG, Lovett EG, Myklebust BM. Measures of postural steadiness: differences between healthy young and elderly adults. IEEE Trans Biomed Eng. September 1996;43(9):956-966.
2009	Winter DA. Biomechanics and Motor Control of Human Movement. 4th ed. Hoboken, NJ: Inc, John Wiley & Sons; 2009.
1991	McGill SM. Electromyographic activity of the abdominal and low back musculature during the generation of isometric and dynamic axial trunk torque: implications for lumbar mechanics. J Orthop Res. January 1991;9(1):91-103.