Anthropometric data

To gain further insight into the mechanisms involved in defective insulin-stimulated glucose uptake in skeletal muscle of insulin-resistant subjects, the possible role of IMCL in the pathogenesis of skeletal muscle insulin resistance and type 2 diabetes mellitus was explored by comparing insulin sensitivity (GIR) and IMCL content of insulin-resistant and insulin-sensitive offsprings of patients with type 2 diabetes. Twenty-six healthy subjects were included in the first study, 13 of them classified as insulin-sensitive and further 13 as insulin-resistant. Metabolic and anthropometric data are given in Table 4. 

An example of the important dynamic data for workplace design is range of joint mohUity (Table 3) which corresponds to postures illustrated in Figure 1. Very useful anthropometric data, both static and dynamic, are provided by the Humanscale (Henry Dreyfuss Associates 1981). When anthropometric requirements for the workplace are not met, biomechanical stresses, which may manifest themselves in postural discomfort, low back pain, and overexertion injury, are likely to occur (Grieve and Pheasant 1982). Inadequate anthropometric design can lead to machine safety hazards, loss of motion economy, and poor visibility. In other words, the consequences of anthropometric misfits may of be a biomechanical and perceptual nature, directly impacting worker safety, health, and plant productivity. 

The concept of normal distribution can used to describe random errors in the measurement of physical phenomena (Pheasant 1989). If tip variable is normally distributed, the population may be completely described in terms of its mean (x) and its standard deviation (s), and specific percentile (X ) values can be calculated, where X = x H- sz, where z (the standard normal deviate) is a factor for the percentile concerned. Values of z for some commonly used percentiles (X ) are given in Table 5. Figure 2 depicts data from Humanscale calculated for different percentiles of U.S. females. A word of caution anthropometric data are not necessarily normaUy distributed in any eiyen population (Kroemer 1989). 

In order to facilitate the application of anthropometric data and biomechanical analysis in workplace design, several computer-based models of man have been developed. These computer-aided tools... 

Safety of machinery—Human body measurements—Part 3 Anthropometric data ISO 7250 1996-07-00 EN ISO 7250 1997-07-00... 

The job severity index (JSI) is a time- and frequency-weighted ratio of worker capacity to job demands. Worker capacity is predicted with the models developed by Ayoub et al. (1978), which use isometric strength and anthropometric data to predict psychophysiceil lifting capacity. JSI and each of the components are defined below. 

Grobelny, J., Anthropometric Data for a Driver s Workplace Design in the AutoCAD System, in Computer-Aided Ergonomics, W. Karwowski, A. Genaidy, and S. S. Asfour, Eds., Taylor Francis, London, pp. 80-89. 

For the design of equipment in human work environments where task analysis is employed, see Human Factors Design Handbook,hyW.E.Woodson [McGraw-Hill, New York, 1981]. For human anthropometric data that are useful to task analysis, see NASA Reference Publication 1024 Anthropometric Source Book, vol 1 Anthropometry for Designers [Webb Associates, Yellow Springs, Ohio, 1978]. 

The human body is subjected to many environmental forces that may be treated as stochastic (random) processes. For example, how would you estimate the forces on an individual during an automobile crash How about the stress on a hip as a person transverses a rocky terrain A second area of interest focuses on the treatment of uncertainties in the measurement of anthropometric data or human performance. Refer to Sec. 31.2.9 ( Human Factors ) for more details. A clinician estimates the mass of a man s arm as 0.4 kg from anthropometric tables, but how do we quantify the effects that might occur due to an error in the estimate One method to quantify the effect of stochastic processes is the Monte Carlo simulation. ... 

Development of sizing systems from anthropometric data... 

The development of a sizing system and identification of control dimensions from anthropometric data requires the efficient manipulation of that data so most of the sample is accommodated in a minimiun number of size categories (Salusso-Deonier, 1985). This is particularly important when body scarmers are used because of the large data sets. 

Table 3.1 Selected anthropometric data sources for military personnel (1960-2010)...

Ashdown, S. R (1998). An investigation of the structure of sizing systems. A comparison of three multidimensional optimized sizing systems generated fiem anthropometric data with the ASTM standard D5585-94. International Journal of Clothing Science and Technology 10(5) 324 1. 

Green, M. E. (1981). An application of U.S. Army women s anthropometric data to the derivation of hypothetical sizing/taritfing systems. Clothing Research Journal 9(1) 16-32. 

Hsu, C.-H. (2009). Developing accurate industrial standards to facihtate production in apparel manufacturing based on anthropometric data. Human Factors and Ergonomics in Manufacturing 19(3) 199-211. 

Lu, J.-M. and M.-J. J. Wang (2007). Automated anthropometric data collection using 3D whole body scanners. Expert Systems -with Applications 35(11-12) 407-14. 

Williams, G. L., 2007. Improving fit through the integration of anthropometric data into a computer aided design and manufacture based design process, PhD Thesis, Loughborough University, Loughborough, UK. http //hdl.handle.net 134/4328 [accessed 15 February 2012]. 

Williams, G. L., Torrens, G. E. and Hodgson, A. R., 2004. Integration of anthropometric data within a computer aided design model, Proceedings-Institution of Mechanical Engineers, PartB Journal of Engineering Manufacture, 218(10), 54. 

The back system s main function is to provide the transfer mechanism between the load shoulder straps and hip belt. Critical in this function, as with shoulder straps and hip belts, is the fit of the back system to the user, ideally using appropriate anthropometric data. The inclusion of stiffened frames (which mechanically join the shoitlder straps and hip belt) has been shown to be one of the most critical inclusions in a LCS design for mitigating injury potential. 

First, differences in drivers anthropometric data, such as height and weight, explain why they do not have the same sensations. For instance, four drivers are not... 

Anthropometric data usually list values for 5th, 50th and 95th percentile males and females. For a given dimension, 95% of the population is larger than the 5th percentile value 95% of the population is smaller than the 95th percentile dimension 50% of the population is larger or smaller than the 50th percentile dimension. 

The primary use of anthropometric data is for fit and reach. However, there are other uses. People come in a variety of sizes and shapes. A few principles apply to the use of... 

Know the population for a design. If there are data for a particular population, a designer can use them. If data are not available for a particular population, a designer must rely on anthropometric data from reference tables. Those data are sources for estimating dimensions and movements of people. Some adjustments may be necessary. 

Most anthropometric data result from particular studies and appear in publications. Some military organizations in the United States and other countries publish anthropometric and ergonomic design standards for military populations. 

Much anthropometric data are in percentiles. Describe how to apply percentile data in design. 

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