Sources of Goniometric Error at the Elbow

Fish, Dale R; Wingate, Lydia

doi:10.1093/ptj/65.11.1666

Cited by 85 publications

(64 citation statements)

References 5 publications

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“…Thus, re-palpation of the bony landmarks and re-positioning of the goniometer between the extended and flexed positions are important in order to minimise measurement error. Both goniometer alignment and landmark identification have been shown to contribute to measurement error in previous studies [9].…”

Section: Discussionmentioning

confidence: 86%

Measurement of knee joint motion using digital imaging

Bennett

Hanratty

Thompson

et al. 2008

International Orthopaedics (SICOT)

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The measurement of joint motion is common practice in many aspects of orthopaedic surgery. A number of techniques and instruments have been developed for this purpose. We describe a method of recording and measuring knee joint motion using digital imaging which demonstrated high inter-observer reliability (r>0.948) and intra-observer repeatability (r>0.906). This technique may offer some practical advantages over other methods of measuring joint motion.Résumé La mesure de la mobilité articulaire est une pratique habituelle en chirurgie orthopédique. De nombreux instruments peuvent être développés. Nous décrivons une méthode de la mesure de la mobilité en utilisant une imagerie digitalisée. Ces techniques montrent une importante sensibilité inter-observateur (r>0,948) et intra observateur avec une bonne répétabilité (r>0,906). En conclusion, cette technique est fiable, répétitive et suffisamment sure offrant un certain nombre d'avantages pratiques.

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Section: Discussionmentioning

confidence: 86%

Measurement of knee joint motion using digital imaging

Bennett

Hanratty

Thompson

et al. 2008

International Orthopaedics (SICOT)

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“…Standard deviations for tendon stiffnesses and muscle moment arms were set to 25 and 20% of the nominal parameter values, respectively (Murray et al 2002;Zajac 1989). Standard deviations for joint angles were set to 4°, the accuracy with which joint posture can be measured with a goniometer (Fish and Wingate 1985;Grohmann 1983). …”

Section: Methodsmentioning

confidence: 99%

Muscle short-range stiffness can be used to estimate the endpoint stiffness of the human arm

Murray

Perreault

2011

Journal of Neurophysiology

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Hu X, Murray WM, Perreault EJ. Muscle short-range stiffness can be used to estimate the endpoint stiffness of the human arm. J Neurophysiol 105: 1633-1641, 2011. First published February 2, 2011 doi:10.1152/jn.00537.2010.-The mechanical properties of the human arm are regulated to maintain stability across many tasks. The static mechanics of the arm can be characterized by estimates of endpoint stiffness, considered especially relevant for the maintenance of posture. At a fixed posture, endpoint stiffness can be regulated by changes in muscle activation, but which activation-dependent muscle properties contribute to this global measure of limb mechanics remains unclear. We evaluated the role of muscle properties in the regulation of endpoint stiffness by incorporating scalable models of muscle stiffness into a three-dimensional musculoskeletal model of the human arm. Two classes of muscle models were tested: one characterizing short-range stiffness and two estimating stiffness from the slope of the force-length curve. All models were compared with previously collected experimental data describing how endpoint stiffness varies with changes in voluntary force. Importantly, muscle properties were not fit to the experimental data but scaled only by the geometry of individual muscles in the model. We found that forcedependent variations in endpoint stiffness were accurately described by the short-range stiffness of active arm muscles. Over the wide range of evaluated arm postures and voluntary forces, the musculoskeletal model incorporating short-range stiffness accounted for 98 Ϯ 2, 91 Ϯ 4, and 82 Ϯ 12% of the variance in stiffness orientation, shape, and area, respectively, across all simulated subjects. In contrast, estimates based on muscle force-length curves were less accurate in all measures, especially stiffness area. These results suggest that muscle short-range stiffness is a major contributor to endpoint stiffness of the human arm. Furthermore, the developed model provides an important tool for assessing how the nervous system may regulate endpoint stiffness via changes in muscle activation. musculoskeletal model WE COMMONLY USE OUR HANDS to move and manipulate objects in different environments. Many of these tasks tend to destabilize arm posture (Rancourt and Hogan 2001). Nevertheless, they can be completed because the central nervous system regulates the mechanical properties of the arm to compensate for these instabilities, usually ensuring that the coupled system of the arm and its environment remains stable so that posture can be maintained (McIntyre et al. 1996). Understanding how this regulation occurs and the relative contributions of the nervous system and the intrinsic biomechanics of the arm remains an important problem in motor control.

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“…The standard deviation of the muscle moment arms was set to 20% of the nominal parameter values (Murray et al 2002). The standard deviation for the joint angles was set to 4°, the accuracy with which angles can be measured with a manual goniometer (Fish and Wingate 1985;Grohmann 1983). Sensitivity analyses were performed only for the first simulation experiment.…”

Section: Methodsmentioning

confidence: 99%

Biomechanical constraints on the feedforward regulation of endpoint stiffness

Murray

Perreault

2012

Journal of Neurophysiology

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Although many daily tasks tend to destabilize arm posture, it is still possible to have stable interactions with the environment by regulating the multijoint mechanics of the arm in a task-appropriate manner. For postural tasks, this regulation involves the appropriate control of endpoint stiffness, which represents the stiffness of the arm at the hand. Although experimental studies have been used to evaluate endpoint stiffness control, including the orientation of maximal stiffness, the underlying neural strategies remain unknown. Specifically, the relative importance of feedforward and feedback mechanisms has yet to be determined due to the difficulty separately identifying the contributions of these mechanisms in human experiments. This study used a previously validated three-dimensional musculoskeletal model of the arm to quantify the degree to which the orientation of maximal endpoint stiffness could be changed using only steady-state muscle activations, used to represent feedforward motor commands. Our hypothesis was that the feedforward control of endpoint stiffness orientation would be significantly constrained by the biomechanical properties of the musculoskeletal system. Our results supported this hypothesis, demonstrating substantial biomechanical constraints on the ability to regulate endpoint stiffness throughout the workspace. The ability to regulate stiffness orientation was further constrained by additional task requirements, such as the need to support the arm against gravity or exert forces on the environment. Together, these results bound the degree to which slowly varying feedforward motor commands can be used to regulate the orientation of maximum arm stiffness and provide a context for better understanding conditions in which feedback control may be needed.

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Sources of Goniometric Error at the Elbow

Cited by 85 publications

References 5 publications

Measurement of knee joint motion using digital imaging

Measurement of knee joint motion using digital imaging

Muscle short-range stiffness can be used to estimate the endpoint stiffness of the human arm

Biomechanical constraints on the feedforward regulation of endpoint stiffness

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