Paper 16.239

D. B. Stefan and D. A. Gilbert, "The Cycle of the Shape Descriptor Suite: When do People Become Overweight?", in Proc. of 7th Int. Conf. on 3D Body Scanning Technologies, Lugano, Switzerland, 2016, pp. 239-254,


The Cycle of the Shape Descriptor Suite: When do People Become Overweight?


David B. STEFAN 1, David A. GILBERT 2

1 Novaptus Systems Inc., Chesapeake VA, USA;
2 The Hague Plastic and Cosmetic Surgery Center, Norfolk VA, USA


Background. An enormous amount of anthropometric data has been collected over the last decade from body scanning morbidly obese subjects prior to bariatric surgery. Even more anthropometric data has been collected by scanning these individuals post-operatively on a periodic basis. A set of shape descriptors and new adiposity indices were developed, previously described and presented. The shape descriptors mathematically classify the shape of the morbidly obese. The adiposity indicators use volume and surface units to define the degree of obesity by determining the "space" occupied versus traditional weight and height and are general in nature. When these formulas are combined and applied to scans covering individuals ranging from visually thin to somewhat obese, an interesting phenomenon occurs. Thin individuals, regardless of gender, have similar shape descriptor values. As these formulas are applied to scans of individuals who appear slightly overweight to noticeably overweight, the shape descriptors begin to mathematically differentiate physical shapes and the ratio of torso volume and torso surface area rapidly changes. The question investigated is whether the start of these changes mark the beginning of being overweight. If unchecked, it could then lead to the onset of the obese condition.
Methods. 3D body scans have been collected at a cosmetic surgery location in parallel with the collection of 3D body scans from various surgical weight loss clinics. In addition, a series of scans were also collected at a local fitness facility. Together, the aggregation of scans analyzed comprised a very good cross-section of body shapes and sizes. The shape descriptor suite and the adiposity indicators were applied to this wide range of body shapes. Height and weight were also tabulated. Successive 3D scans from extremely thin to morbidly obese provided a progressive simulation of healthy and unhealthy weight gain.
Results. The point, or rather points, where the shape descriptors begin to differentiate body shapes has a great deal to do with weight distribution. Proportionately thin females and males generally have a maximum torso circumference height near or at the hips measurement location. Thin individuals register high on the shape descriptor scale and have a greater preponderance of torso surface area vs. torso volume. As more girth is visually apparent, the maximum torso slice circumference begins to move upward, and the individual's torso volume increases at a greater pace than their torso surface area. There appears to be boundary points where these shape formulas become valid. Individuals of both sexes who are extremely thin have similar mathematical shape values. These are the upper boundaries where the formulas do not apply.
Discussion. As weight gain becomes distributed on the body, females have a tendency to store fat around the hips, while males begin to exhibit weight gain in the abdominal area. There is a "normal" range for the healthy weight males and females as exhibited by their torso volume/torso surface area ratio. At a particular point outside this normal range, the rate of torso volume increases more than the rate of torso surface area. This raises the ratio and a shift in the maximum torso circumference height changes the shape descriptors. The combination of these detectable characteristics derived from 3D body scanning might be utilized to reveal insights into the onset of physical changes in the body. As such 3D body scanning could be a useful health and fitness "early warning" monitoring tool for the population at large.


Full paper: 16.239.pdf
Proceedings: 3DBST 2016, 30 Nov.-1 Dec. 2016, Lugano, Switzerland
Pages: 239-254
DOI: 10.15221/16.239

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