The technique as described here shows how relations between individual body measurements can be determined and used in the design of three-dimensional products.
As was said before: the average person does not exist; therefore the use of one-dimensional data to determine product dimensions can easily lead to unwanted situations. The techniques of two-dimensional anthropometry allow you to get insight in the correlations between two different body dimensions. By that it can show the consequences for related body dimensions. However, this can only be done well in a 2D window, to get insight in a 3D problem it is therefore needed to switch regularly between these windows
Data to use for this technique can be obtained from the same measurements as for 1D anthropometry. However, to determine correlations between different dimensions individual measurements of participants are needed.
- Obtains useful information from a product design perspective
- Gives insight in correlation
- Gives insight in consequences for related product dimensions
- Limited to two dimensions at a time
- Requires original datasets with individual measurements
How to use two-dimensional data
There are a variety ways to work with two-dimensonal data. For product design it is generally easiest to do so visually. To make it easy, DINED has a tool available specifically for analysing two-dimensional data.
Ellipse allows you to get insight in the correlation between two different body dimensions. Based on the rough data of these two body dimensions, Ellipse draws a clear graph, a scatter plot. The shape of the data cloud provides insight in the dimensions’ correlation (circular: low correlation, elliptical: some correlation, almost a line: high correlation). This set of data points in 2D will show designers the consequences for related product dimensions for their design topic at hand.
The following questions might be answered with Ellipse:
- How to address all users of my target group?
- Is it possible to make one solution for all?
- Or do I need to make a small, medium and large version?
- Or better to make my product adjustable over a certain range?
Correlations are useful because they can indicate a predictive relationship between measurements. This can be useful for instance when data about a specific body dimension is not available in a particular data set but a strongly related dimension is.
Additionally, an earlier version of Ellipse is available for download (Windows only). This version allows you to import custom data. See Raw data for a limited set of studies to use with this version of Ellipse.
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