The use of magnetic resonance imaging for measuring segment inertial properties

Martin, Philip E.; Mungiole, Michael; Marzke, Mary W.; Longhill, Julie M.

doi:10.1016/0021-9290(89)90051-1

Cited by 97 publications

(57 citation statements)

References 8 publications

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“…Previous studies have used medical imaging and scanning systems (DEXA, MRI and CT) to obtain accurate subject specific BSP estimates [8][9][10][11]. However, the required investment [11], lengthy scan time of MRI [11], and health risks of DEXA and CT [9] have led to their criticism as viable methods.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters

Clarkson

Wheat

Heller

et al. 2015

Lecture Notes in Computer Science

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Section: Introductionmentioning

confidence: 99%

“…However, the required investment [11], lengthy scan time of MRI [11], and health risks of DEXA and CT [9] have led to their criticism as viable methods.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters

Clarkson

Wheat

Heller

et al. 2015

Lecture Notes in Computer Science

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“…Various techniques available for estimating the inertial properties of a fully intact human body segment include: 1) regression equations based on cadaver data [1][2][3][4][5] , 2) mathematical models (i.e., geometric models) 6,7 , and 3) scanning & imaging techniques [8][9][10][11][12][13][14][15] . Many of these techniques require direct measurements from the body, but it has previously been shown that regardless of the estimation method being used, the precision of body segment inertial estimates based on these methods is high 16 .…”

Section: Introductionmentioning

confidence: 99%

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis

Smith

Ferris

Heise

et al. 2014

JoVE

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The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.

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“…Unlike other methods, CT or MRI scans provide information about internal structures such as tissue composition which should improve the reconstruction accuracy (Martin et al, 1989;Mungiole & Martin, 1990;Pearsall, Reid & Livingston, 1996;Bauer et al, 2007). These approaches are, however, also difficult to implement in large-scale studies due to cost and ethical constraints.…”

Section: Introductionmentioning

confidence: 99%

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

Peyer

Morris

Sellers

2014

Preprint

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Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. These quantities are, however, not directly measurable. Current approaches include using regression models which have limited accuracy; geometric models with lengthy measuring procedures; or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multicamera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

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The use of magnetic resonance imaging for measuring segment inertial properties

Cited by 97 publications

References 8 publications

Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters

Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters

Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis

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

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