Literature DB >> 7872577

Inertial properties of the human trunk of males determined from magnetic resonance imaging.

D J Pearsall1, J G Reid, R Ross.   

Abstract

The purpose of this study was to evaluate the segmental parameters of the human trunk of males in vivo using magnetic resonance imaging (MRI). In addition, the efficacy of volumetric estimation and existing prediction formulas to produce segmental properties similar to those produced by MRI was evaluated. As opposed to finding one representative normal value for these parameters, a range of normal values was defined. For instance, the average trunk mass was 42.2% +/- 3.5% (x +/- SD) of body mass, but values ranged from 35.8% to 48.0%. To account for segment parameters more accurately, specific anthropometric measures need to be considered in addition to overall measures of body height and mass. These specific measures included segment length, circumference, width, and depth. Studies reporting general percentages based on height and/or mass were found to be inadequate predictors of segmental parameters of the trunk compared with MRI estimates. Volume-based estimates, which assume a uniform density distribution within a segment, were found to correspond closely to MRI values except for the thorax. However, the use of density values reflective of the living in vivo state would likely alleviate this disparity, thus indicating that the volumetric technique may be effective for deriving segmental parameters for large segments of the trunk. Future research should adopt noninvasive techniques such as MRI and/or volumetric estimation to enhance the predictability of segmental parameters of the body for specific population groups characterized by gender, developmental age, body type, and fitness level. Further efforts should be made to establish standardized boundary definitions for trunk segments to avoid unnecessary confusion, from which substantial errors may be introduced into biomechanical linked-segment analyses of human movement.

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Year:  1994        PMID: 7872577     DOI: 10.1007/bf02368294

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  18 in total

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  11 in total

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Authors:  Sara L Matrangola; Michael L Madigan; Maury A Nussbaum; Robert Ross; Kevin P Davy
Journal:  J Biomech       Date:  2008-10-17       Impact factor: 2.712

10.  Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras.

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