Determination of Bicycle Handle Diameters considering Hand Anthropometric Data and User Satisfaction

Abstract

Ergonomic product design considering both anthropometric variability and user preference is required for harmonizing the target users and products. In this study, bicycle handle diameters for three size categories were determined by considering anthropometric variability and preference. To design the bicycle handles, a four-step process was applied: (1) define anthropometric data, (2) develop size chart, (3) define a design equation, and (4) determine design values. In the first step, the 1988 US Army data was chosen as anthropometric data for the design target population. In the second step, to develop a size chart of bicycle handle, hand length and circumference were selected as key dimensions by principal component analysis on six representative hand dimensions. Next, a size chart of three categories (small: 175.5 mm, medium: 186.7 mm, and large: 196.2 mm) were derived by K-means clustering analysis for hand length and circumference. In the third step, the design equation accounting geometrical relationship between the sizes of two key dimensions and diameters of bicycle handle was adopted from a relevant existing research. In the last step, design values (40.9 mm, 43.5mm, and 45.7 mm) for each size category were calculated by inputting the sizes of the key dimensions to the design equation. To evaluate user satisfaction level of the bicycle handles, a user testing of three handle prototypes was conducted for 17 participants with various hand sizes. The test results showed that satisfaction scores for each hand group were significantly higher at the corresponding size category.

Ergonomic design of an EEG headset using 3D anthropometry

“…By using the statistical shape model of the scalp, a number of time-consuming steps from traditional anthropometry could be omitted. For example, there was no need to limit the fit to a single measurement such as circumference, or to create a design equation in order to link this measurement to a CAD product (as in (Chang et al, 2010)). Nor was there a need to interpolate the remaining head shape once an appropriate number of mannequins for these measurements were created (as in (Ball, 2009)).…”

“…Ergonomics deals with the implementation of this knowledge in order to make better fitting products. In ergonomic product design, descriptive statistics (most commonly mean and standard deviation) are performed on a number of anthropometric measurements and a design equation is created to link these measurements to the shape and size of the product (Chang et al, 2010;Luximon et al, 2012). For example, in the design of helmets, the head circumference is often used.…”

Product sizing with 3D anthropometry andk-medoids clustering

“…The product dimensions for each product size are based on the percentage of the population that has predetermined measurement values, e.g. for a product with three sizes the 5th, 50th and 95th percentile (respectively P5, P50, P95) are commonly used [1,3,4]. While this method has been the industry standard for quite some time, it does not take into account the correlation between various body measurements.…”

“…The required number of product sizes depends on the total percentage of the population covered by all sizes, also called the accommodation rate. Once the required number of sizes is known, products are modeled according to the manikins for each size and a design equation is determined in order to assign anthropometric measurements to different product sizes [3,4]. Even with multivariate sizing, however, this often results in an incorrect fit [6,7].…”

“…When PCA is used for dimensionality reduction, the elements on the main diagonal of S 2 are added until a desired percentage of total variance is reached, and all remaining shape modes are discarded [5]. While there is a number of methods to determine which principal components are most relevant to the shape variation [5], a generally accepted method is to select those components that explain a cumulative percentage of the population [20,21,4,6,22]. A threshold between 70% and 90% is sufficient for most applications [23].…”