Error detection in three-dimensional surface anthropometric data

In recent years, the use of three-dimensional surface anthropometry has facilitated the collection of anthropometric data. Given the importance of reducing errors and securing data quality, data checking procedures are necessary. After an influential study done by Fellegi, I.P., Holt, C. [1976. A systematic approach to automatic edit and imputation. Journal of the American Statistical Association 71, 17-35], many survey organizations adopted data checking procedures to determine whether data are reliable or not. Detection of erroneous data is an essential part of data checking. An important feature of anthropometric data is that the data are continuous and multivariate and have strong correlations among variables. Because of the patterns of intermittent errors in multivariate data, data checking can be very complicated. The objective of this study is to propose an error detection procedure that uses a dynamic and interactive graphical method for anthropometric data. Furthermore, we present the results from applying this procedure to the data from the Korean National Anthropometric Survey, Size Korea 2004. Relevance to industry: Anthropometric data provide a valuable source of information to ergonomists and designers. The results of this study can help to increase the reliability of anthropometric data collected by three-dimensional measurement approaches.