Indonesian anthropometry update for special populations incorporating Drillis and Contini revisited

Abstract

a b s t r a c tNowadays, research on anthropometry becomes more essential, and yet, it is critical due to its implication and contribution to product and system design. Since it deals with human capability and limitation on physical activities, its role becomes more important, especially, when it comes to the needs for special populations. This study provides a comparative study between elderly and children anthropometry using Drillis and Contini approach incorporating Chinese and non-Chinese ethnic groups. More than 1000 subjects involved in this study. After the data refinement process, there were 498 valid data for children (i.e., 98 Chinese male, 136 non-Chinese male, 134 Chinese female, and 130 non-Chinese female), and 556 valid data for elderly (i.e., 186 Chinese male, 148 non-Chinese male, 115 Chinese female, and 107 non-Chinese female).In general, the finding shows that elderly (both male and female, both Chinese and non-Chinese) tends to have similar size and pattern with adult. Whilst, male and female children of 6e9 years sub-group (both Chinese and non-Chinese sub-group) tend to have higher weight ratio, compared to elderly and the children of 10e12 years sub-group. It was easily recognized that the children tend to have higher rate for limb segments compared to other body dimensions. At all sample groups, the eye height and shoulder height were found to be highly correlated with stature. Moreover, related to body weight, all samples show that thigh thickness and abdominal depth were deemed to be significant measures to be associated with.The expected contribution of this study is that to update the Indonesian special population anthropometry and to identify which measures are significantly associated with stature and weight, respectively with regard to different special population and given limited anthropometric data. Practically, given the data of stature and body weight, product designer can predict the anthropometric characteristics for special population.

2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

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