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Predicting body composition using simple measurement techniques

Predicting body composition using simple measurement techniques. Tim Johnson, Javier Navarro, Idiong idongesit , Mark Weeks. Data .

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Predicting body composition using simple measurement techniques

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  1. Predicting body composition using simple measurement techniques Tim Johnson, Javier Navarro, Idiongidongesit, Mark Weeks

  2. Data • in 1985 a study about predicting body fat distribution from easily obtainable measurements was undertaken. 252 male subjects volunteered for the study. Over the years one instance was lost. • records were recorded for the following vital statistics: Items 6-15 measured in centimeters

  3. Calculations Density Body Fat percentage where, A= proportion of lean body tissue a= density of lean ~1.1 gm/cm3 B= proportion of fat body tissue b= density of fat ~0.90 gm/cm3 AND % Body Fat = 495/D – 400 OR B = (1/D)*[ab/(a-b)]-[b/(a-b)] where, W is weight in water or air c.f. is water temperature correction factor ~.997 at 76-78 degrees Fahrenheit This method of determining D, density, is considered the gold standard.

  4. Equation developed for Lean Body Weight LBW=17.298 <numerical offset> +.89946(Weight) -.2783(age) +.002617(age)2 <Age factor> +17.819(Height) <Height factor> -.6798(Waist-Wrist) Stepwise multiple regression techniques were used to develop this structural equation back in the 1980’s.

  5. Overview of the data

  6. How does age compare to Density

  7. How Does Height compare to Density?

  8. Age vs Weight

  9. Height vs Weight

  10. Weight vs Neck

  11. Weight Vs Density

  12. Density VS Waist

  13. How does age compare to %Body Fat

  14. Training Set Density Distribution

  15. Training set %BodyFatDistribution

  16. Test set’s %BodyFat Distribution

  17. Simple Linear Regression

  18. Visualize errors

  19. Health Freak

  20. Consider this • The previous nearly perfect prediction looses the ease of prediction using simple measurement techniques. The Formula also uses the gold standard: Density as the basis for the prediction. • Can simple measurement techniques predicting %Bodyfat be found using WeKA? • The following slides check out that possibility • First using the Waist measurement • Then using the waist and the wrist measurements • And finally using all the measurements but Density

  21. Training set waist

  22. Training Set Waist & wrist

  23. Training Set all but…

  24. Could we duplicate the 1985 Results?

  25. One measurement Body Fat

  26. Two measurement Body Fat

  27. All But predict Body Fat

  28. 1985

  29. Using M5P Rules Here we use machine learning to develop rules: Weka detects two using waist > or < 87.1 cm circumference. Overall accuracy is at a regression value of 85.33%

  30. Clustering—simple K means

  31. Summary • The formula with the Best results based its predictive ability upon the Density of the individual in air and water. • We lose the goal of the 1985 study of being able to predict the percent of body fat based on easily accessible measurements. • By Eliminating the Density category the Calculation Engine is forced to utilize the remaining categories. • The resulting Correlation probability show the accuracy attained using easily obtainable measurements without over fitting. • Some evidence of clustering was found and compared to the Rules.

  32. References • “Generalized Body composition prediction equation for men using simple measurement techniques” K. W. Penrose, et al. FACSM, Human Performance Research Center, Brigham Young University, “Medicine and Science in sports and Exercise, V17, No. 2, April 1985, p. 189. • “Bodyfat”, R.W.Johnson, Dept of mathematics & computer Science, South Dakota School of Mines and Technology, Hosted by StatLIB, Department of Statistics, Carnegie Mellon University, http://lib.stat.cmu.edu/modules.php, accessed 3/23/2014.

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