Segment inertial properties of Chinese adults determined from magnetic resonance imaging

Cheng, Cheng‐Kung; Chen, Hsiang Ho; Chen, Chen Sheng; Lee, Chen Lung; Chen, Chih Yong

doi:10.1016/s0268-0033(00)00016-4

Cited by 128 publications

(93 citation statements)

References 20 publications

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“…This method of obtaining paraspinal muscle CSA and FCSA could also have application in the determination of segmental inertial parameters of the trunk, head and neck [3,32]. A method to determine the correct grey scale range for the MR signals emitted by various body tissues would increase the accuracy of these measurements.…”

Section: Methods Applicationmentioning

confidence: 99%

“…Segmentation is a complex area in automated MR image analysis due to potential problems such as heterogeneous signal intensities in tissues and the possibility that individual pixels of an MR image may contain two or more anatomical structures (the partial volume effect) [1,10,14,26,34]. Regardless of these concerns, recent investigations using MR imaging to determine inertial properties of body segments have identified tissue types using discrete grey scale ranges for signal intensity emitted by various tissues including fat, bone and muscle [3,32]. More sophisticated methods of MR image tissue segmentation have been successfully utilised in the area of brain research.…”

Section: Introductionmentioning

confidence: 99%

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An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles

et al. 2005

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The purpose of this study was to investigate the use of magnetic resonance (MR) imaging and image processing software to determine the functional cross-sectional area (FCSA) (the area of muscle isolated from fat) of the lumbar paraspinal muscles. The measurement of the morphology of the lumbar paraspinal muscles has become the focus of several recent investigations into the aetiology of low back pain. However, the reliability and validity of determining the FCSA of the lumbar paraspinal muscles using MR imaging are yet to be reported. T2 axial MR scans at the L1-S1 spinal levels of six subjects were obtained using identical MR systems and scanning parameters. Lean paraspinal muscle, vertebral body bone and intermuscular fat were manually segmented using image analysis software to assign a grey scale range to the MR signal intensity emitted by each tissue type. The resultant grey scale range for muscle was used to determine FCSA measurements for each of the paraspinal muscles, psoas, quadratus lumborum, erector spinae and lumbar multifidus on each scan slice. As various biological, instrument and measurement factors can affect MR signal intensity, a sensitivity analysis was conducted to determine the error associated in calculating FCSA for paraspinal muscle using a discrete grey scale range. Cross-sectional area and FCSA measurements were repeated three times and reliability indices for the FCSA measurements were obtained, showing excellent reliability, intra class correlation coefficient (mean=0.97, range 0.90-0.99) and %SEM (mean=2.6%, range 0.7-4.8%). In addition, the error associated with miscalculation of the grey scale range for the MR signal intensity of muscle was calculated and found to be low with an error of 20 grey scale units at the upper end of the muscle's grey scale range resulting in a very small error in the measured muscle FCSA. The method presented in this paper has a variety of practical applications in areas such as evidence-based rehabilitation, biomechanical modelling and the determination of segmental inertial parameters.

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Section: Methods Applicationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles

et al. 2005

View full text Add to dashboard Cite

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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%

“…However, the use of models and historical data results in BSPs of an inherently generic nature [15]. Such methods are also criticised as the data underpinning the models typically comes from small sample groups [16] that have a lack of gender and racial diversity [10], and is therefore unrepresentative of the wider population.…”

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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“…After successful compilation steps 1, 2, and 3 on data, step to construct the human skeleton model by using the following function, seen in Figure 6. mcplotframe (walkm,180, mapar); (3) There are many methods [21][22][23][24][25][26][27][28][29][30][31] to compute the human body segment parameters. They have trendy source of BSP knowledge of human body.…”

Section: ) First Access the Index Of Motion Sensors Which Are Placedmentioning

confidence: 99%

A New Bio-Informatics Framework: Research on 3D Sensor Data of Human Activities

Ali¹,

Wu²,

Khan³

et al. 2015

ijacsa

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Abstract-Due to increasing attraction of motion capture systems technology and the usage of captured data in wide range of research-oriented applications, a framework has developed as an improved version of MOCAP TOOLBOX in Matlab platform. Firstly, we have introduced a faithful script to deal with public motion capture data, which will be friendly for us. Various functions through dynamic programming, by using the Body Segment Parameters (BSP) are edited and they configured the position of markers according to data. It is used to visualize and refine without the MLS view and the C3D editor software. It has opened a valuable way of sensor data in many research aspects as gait movements, marker analysis, compression and motion pattern, bioinformatics, and animation. As a result, performed on CMU and ACCAD public mocap data, and achieved higher corrected configuration scheme of 3D markers when compared with the prior art, especially for C3D file. Another distinction of this work is that it handles the extra markers distortion, and provides the meaningful way to use captured data.

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Segment inertial properties of Chinese adults determined from magnetic resonance imaging

Cited by 128 publications

References 20 publications

An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles

An investigation into the use of MR imaging to determine the functional cross sectional area of lumbar paraspinal muscles

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

A New Bio-Informatics Framework: Research on 3D Sensor Data of Human Activities

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