Towards a realistic biomechanical model of the thumb: the choice of kinematic description may be more critical than the solution method or the variability/uncertainty of musculoskeletal parameters

Valero-Cuevas, Francisco J.; Johanson, M. Elise; Towles, Joseph D.

doi:10.1016/s0021-9290(03)00061-7

Cited by 186 publications

(194 citation statements)

References 32 publications

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“…In modeling, simplifying the thumb CMC joint as a ball-and-socket articulation rather than with the more complex harmonic profiles we identified, where the location of the screw axis can vary by >1 cm, could lead to substantial errors in the computation of ligament strains, cartilage stresses, and muscle moment arms. A recent musculoskeletal model of the thumb has demonstrated that simplified modeling of the CMC joint as a 2DOF structure does not accurately predict the muscle forces at the thumb tip [46]. It is possible that the kinematic model presented here could improve the accuracy of such musculoskeletal models of the thumb.…”

Section: Discussionmentioning

confidence: 97%

The Envelope of Physiological Motion of the First Carpometacarpal Joint

Crisco

Patel

Halilaj

et al. 2015

Journal of Biomechanical Engineering

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Much of the hand's functional capacity is due to the versatility of the motions at the thumb carpometacarpal (CMC) joint, which are presently incompletely defined. The aim of this study was to develop a mathematical model to completely describe the envelope of physiological motion of the thumb CMC joint and then to examine if there were differences in the kinematic envelope between women and men. In vivo kinematics of the first metacarpal with respect to the trapezium were computed from computed tomography (CT) volume images of 44 subjects (20M, 24F, 40.3 6 17.7 yr) with no signs of CMC joint pathology. Kinematics of the first metacarpal were described with respect to the trapezium using helical axis of motion (HAM) variables and then modeled with discrete Fourier analysis. Each HAM variable was fit in a cyclic domain as a function of screw axis orientation in the trapezial articular plane; the RMSE of the fits was 14.5 deg, 1.4 mm, and 0.8 mm for the elevation, location, and translation, respectively. After normalizing for the larger bone size in men, no differences in the kinematic variables between sexes could be identified. Analysis of the kinematic data also revealed notable coupling of the primary rotations of the thumb with translation and internal and external rotations. This study advances our basic understanding of thumb CMC joint function and provides a complete description of the CMC joint for incorporation into future models of hand function. From a clinical perspective, our findings provide a basis for evaluating CMC pathology, especially the mechanically mediated aspects of osteoarthritis (OA), and should be used to inform artificial joint design, where accurate replication of kinematics is essential for long-term success.

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Section: Discussionmentioning

confidence: 97%

The Envelope of Physiological Motion of the First Carpometacarpal Joint

Crisco

Patel

Halilaj

et al. 2015

Journal of Biomechanical Engineering

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“…Due to parameter variability and covariance, it is advantageous to measure parameters in conjunction with one another, rather than to use parameters from different data-sets (Hoffer et al, 1989;Hoy et al, 1990;Loren et al, 1996). In addition, stochastic musculoskeletal models (Hughes and An, 1997;McLean et al, 2003;Valero-Cuevas et al, 2003;Davidson et al, 2004) require parameter distributions. Measuring all parameters on the same specimens will allow for determination of parameter covariance.…”

Section: Introductionmentioning

confidence: 99%

Variability in isometric force and moment generating capacity of glenohumeral external rotator muscles

Langenderfer

Patthanacharoenphon

Carpenter

et al. 2006

Clinical Biomechanics

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Background. Muscles which cause glenohumeral external rotation possess varying ability for generating force and moment due to differences in muscle architecture, moment arm, and the interaction of these two factors. This study's purpose was to determine a complete dataset of muscletendon parameters for predicting the moment generating capacity and force-length dependence for external rotation of infraspinatus, supraspinatus and teres minor muscles.Methods. Muscle fascicle length, sarcomere length, pennation angle, and muscle volume were measured for sub-regions of infraspinatus and supraspinatus, and teres minor from 10 glenohumeral specimens. Tendon excursion was measured for glenohumeral rotation. From these parameter measurements, optimal fascicle length, physiological cross-sectional area, muscle force-length dependence, and maximum isometric moment generating capacity were calculated.Findings. Substantial differences were found for optimal muscle length, physiologic cross-sectional area, and tendon length for the 10 specimens of this study. Muscle sub-region had a significant effect on the force-length relationship for infraspinatus (P < 0.001), but was not significant for supraspinatus (P = 0.49). For infraspinatus and supraspinatus, maximum isometric rotation moment capacity was greater at 10° versus 60° abduction (P < 0.001). Maximum isometric rotation moment capacity for the teres minor was greater at 10° versus 60° abduction (P < 0.01). Sub-regions demonstrated significant differences in isometric moment capacity (P < 0.001).Interpretation. Functional capabilities of these muscles depend on muscle architecture and moment arm as well as their combined effects. The results allow for development of stochastic and deterministic models of glenohumeral external rotation strength which can be used for prediction of muscle forces and joint moments.

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“…The dorsal premotor cortex (PMd) has been studied most frequently during reaching (Cisek and Kalaska 2005;Hatsopoulos et al 2004;Weinrich et al 1984) and the ventral premotor cortex (PMv), most frequently during grasping (Carpaneto et al 2011;Fluet et al 2010;Raos et al 2006;Rizzolatti et al 1988;Spinks et al 2008). A number of studies have shown, however, that many neurons in PMd and PMv vary their discharge in relation to both the location of reaching and the object grasped (Bansal et al 2012;Raos et al 2004;Stark et al 2007;Wu and Hatsopoulos 2007), calling into question the notion that PMd controls reaching, whereas PMv controls grasping.…”

Section: Implications For the Neural Control Of Reach-to-grasp Movementsmentioning

confidence: 99%

“…The problems of relating the activity of various muscles to the mechanics of the grasping hand are complex (Schaffelhofer et al 2015;Towles et al 2013;ValeroCuevas 2005;Valero-Cuevas et al 2003). Nevertheless, when 6 -8 objects, which differ in size and shape, are all presented at the same location, the object that is being grasped can be decoded from the EMG activity of 8 -12 forearm and intrinsic hand muscles (Brochier et al 2004;Fligge et al 2013).…”

mentioning

confidence: 99%