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Steven J. Obst, Lee Barber, Ashton Miller and Rod S. Barrett

Estimates of in vivo Achilles tendon (AT) force are needed to measure tendon mechanical properties as a function of the measured net ankle joint torque, and to understand AT function using musculoskeletal modeling approaches. The AT moment arm is required to convert the measured external ankle

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Sabrina S.M. Lee, Gregory S. Lewis and Stephen J. Piazza

The accuracy of an algorithm for the automated tracking of tendon excursion from ultrasound images was tested in three experiments. Because the automated method could not be tested against direct measurements of tendon excursion in vivo, an indirect validation procedure was employed. In one experiment, a wire “phantom” was moved a known distance across the ultrasound probe and the automated tracking results were compared with the known distance. The excursion of the musculotendinous junction of the gastrocnemius during frontal and sagittal plane movement of the ankle was assessed in a single cadaver specimen both by manual tracking and with a cable extensometer sutured to the gastrocnemius muscle. A third experiment involved estimation of Achilles tendon excursion in vivo with both manual and automated tracking. Root mean squared (RMS) error was calculated between pairs of measurements after each test. Mean RMS errors of less than 1 mm were observed for the phantom experiments. For the in vitro experiment, mean RMS errors of 8–9% of the total tendon excursion were observed. Mean RMS errors of 6–8% of the total tendon excursion were found in vivo. The results indicate that the proposed algorithm accurately tracks Achilles tendon excursion, but further testing is necessary to determine its general applicability.

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Stephen J. Pearson, Tim Ritchings and Ahmad S.A. Mohamed

The work describes an automated method of tracking dynamic ultrasound images using a normalized cross-correlation algorithm, applied to the patellar and gastrocnemius tendon. Displacement was examined during active and passive tendon excursions using B-mode ultrasonography. In the passive test where two regions of interest (2-ROI) were tracked, the automated tracking algorithm showed insignificant deviations from relative zero displacement for the knee (0.01 ± 0.04 mm) and ankle (–0.02 ± 0.04 mm) (P > .05). Similarly, when tracking 1-ROI the passive tests showed no significant differences (P > .05) between automatic and manual methods, 7.50 ± 0.60 vs 7.66 ± 0.63 mm for the patellar and 11.28 ± 1.36 vs 11.17 ± 1.35 mm for the gastrocnemius tests. The active tests gave no significant differences (P > .05) between automatic and manual methods with differences of 0.29 ± 0.04 mm for the patellar and 0.26 ± 0.01 mm for the gastrocnemius. This study showed that automatic tracking of in vivo displacement of tendon during dynamic excursion under load is possible and valid when compared with the standardized method. This approach will save time during analysis and enable discrete areas of the tendon to be examined.

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Laura C. Slane, Stijn Bogaerts, Darryl G. Thelen and Lennart Scheys

Chronic tendon injuries, such as tendinopathy, commonly occur in energy-storing tendons and can have a high socioeconomic impact on the general population, both in terms of lost work and the effects on normal daily living. 1 Intriguingly, tendinopathies often arise in consistent locations

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Keith Baar

due to the high playing load and intensity. In a preliminary report from the Australian National Basketball League, 52.3% of players reported patellar tendon pain that limited performance ( Hannington et al., 2017 ), suggesting that the prevalence of this injury is high at the elite level. Typically

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Tijs Delabastita, Stijn Bogaerts and Benedicte Vanwanseele

In the human body, the forces produced by muscle-tendon units are transmitted to the skeleton through tendons. Because of their elastic properties, they allow energy storage and return during functional activities. As a result, the tendon decouples the muscle fascicle length changes from the total

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Jared R. Fletcher and Brian R. MacIntosh

Direct measurement of muscle forces in vivo is highly invasive, 1 so muscle forces are typically estimated from measurement of joint moments. 2 , 3 Estimating muscle forces from joint moments requires knowledge of the muscle/tendon moment arm, that is, the perpendicular distance from the joint

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Carly C. Sacco, Erin M. Gaffney and Jesse C. Dean

. While less well studied than tactile enhancement, stochastic resonance can also be used to enhance muscle proprioceptive feedback. Early human 19 and animal 20 experiments found that white noise tendon vibration increases the stretch-sensitivity of muscle spindles embedded in the vibrated

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Christopher Tack, Faye Shorthouse and Lindsy Kass

[“what is the effect of dietary supplements on musculoskeletal tissue (e.g., cartilage, tendon, muscle, ligament) healing compared to placebo or other control?”] and was used to formulate a search of Google Scholar and PubMed to evaluate the quality/volume of the existing literature. This search produced

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Kurt Manal and Thomas S. Buchanan

Tendon develops force proportional to the distance it is stretched beyond its slack length. Tendon slack length is an important parameter for musculoskeletal models because it can greatly affect estimations of muscle force. Unfortunately, tendon slack length is a difficult parameter to measure, and therefore values for it are not often reported in the literature. In this paper we present a numerical method for estimating tendon slack length from architectural parameters of the muscle. Specifically, tendon slack length is computed iteratively from musculotendon lengths determined when a corresponding joint is held at two angles, and from knowledge of the muscle's optimal fiber length. Idealized data generated using SIMM were used to test the tendon slack length algorithm. The method converged to within 1% of the “true” tendon slack length specified in the SIMM model. The advantage of the method outlined in this paper is that it yields subject-specific estimates of tendon slack length, given subject-specific input parameters.