We apply anthropometry knowledge and technology to develop novel products and services with good fitting attributes for the target population following different market strategies:
- Product selection (ergonomic benchmarking)
- Size allocations problem
- Optimisation of sizing systems
We follow user-centred design methods to implement anthropometric data in the design process:
- User-product interaction. We develop and apply methodologies to analyse the fit perception and the mechanical interaction of wearable products.
- Ergonomic design rules. We use statistical methods to relate product features (e.g. dimensions or materials) with human body (e.g. measurements or shapes).
What is SUNfeet?
SUNfeet is a fusion of new trends in health, technology and fashion to develop customized insoles for improved shoe comfort. Now your feet will follow your lifestyle.
This smartphone-based technology for 3D measurement of your feet and its innovative design have been developed by the Instituto de Biomecánica . A semi-flexible support customized to your feet’s anatomy and manufactured with rapid manufacturing technology reduces fatigue and pain appearing on the sole of the foot during the day.
How to get your SUNfeet insoles?
How the customized insoles are manufactured?
Rapid manufacturing technologies enable an optimal production of customized insoles in small batches. New materials, suitable to be processed with this technology, have been tested in terms of functionality, comfort and durability.
Development of Sizing recommendation systems
Bad fit is the cause for return in approximately 75% of sales, being mostly due to the confusing garment sizing and label systems and to the low reliability of the advising method to select the proper size at home.
We developed in cooperation with ZARA a pilot test to analyze the factors that influence a proper size recommendations and viability to predict the garment fitting in different areas from anthropometric data of the user.
Samples of the pilot test
The pilot test was done with a blazer, a skirt and two trousers.
It consisted on subjective fitting tests and a 3D body scanning session to obtain the digital anthropometry. Fifty females from 18 to 35 participated in the experimentation For each garment, the participants tried on their respective right size, one size up and one size down.
The user and an expert on garment design filled out a questioner to gather the following information:
- Fitting perception on main body parts of the garment
- Fitting preference on main body parts of the garment
- User’s size
- Global fitting score
The multinomial logistic regression model was applied in two steps. First, it is predicted the fitting on key body areas and secondly it is calculated the best fitting size.
The success rate of the multivariant models is 85-93%, which is higher than the usual size allocation charts.
Alemany, S., Ballester, A., Parrilla, E., Uriel, J., González, J., Nácher, B., González, J.C., Page, A.
4th International Conference on 3D Body Scanning Technologies, Long Beach, CA, USA. November 2013.
Wearable technology requires optimal sizing of the garment and a precise location of sensors to achieve an accurate performance. The following case study was developed for the company Nuubo shows the contribution of anthropometry and body shape analysis to design a smart T-shirt that monitors electro cardiogram (ECG) in real time.
1) Precise anatomic location of sensors on contact points.
2) Optimum sizing system and precise selection process of the size based on anthropometry.
12 subjects with different morphotypes of the torso took part in the experimentation:
- Determination of pressure thresholds: Essential to achieve a high quality measurement of heart rate and maximum for comfort and usability (put on and take the shirt). A mat of pressure sensors was used to measure the pressure distribution in the target areas of the torso.
- Determination of the contact areas of the body: With the analysis of the body shape variation using a 3D database of the target population and thermal maps of users wearing the instrumented T-shirt. The aim is to locate the areas of the torso that assure a good contact of the electrocardiogram sensors.
- Mechanical testing of the textile material: The mechanical characterization enables the estimation of the pressures over the body related to the textile deformation. These results combined with the pressure threshold were used to define the distribution of sizes.
How to use anthropometry to design an ergonic product?
How to use anthropometry to design an ergonomic product? The implementation of anthropometry in the product geometry and design is not straightforward. It depends on many factors such as type of fitting (e.g. tight, loose), deformation of the materials in the interface or type usage.
In this case study we propose a new methodology to generate design criteria for optimum fitting of helmets based on a multidimensional approach relating geometry (interferences: anthropometry of the head versus inner shape of the helmet), pressure interaction and subjective perception.
1) Methdology to obtain the geometric interferences
The geometric interferences are the areas of the head in tight contact with the helmet. The alignment of the 3D head and the helmet uses a scan of the user wearing the helmet as a reference. Four reference points marked and rigidly attached to the external surface of the helmet were used to perform the registration of the 3D CAD model of the helmet and the scan of the subject wearing the helmet. The registration of the single scan of the head and the scan of the subject wearing the helmet was based on three common anatomical landmarks: left and right ectocanthion (most external point of the orbital) and pronasale (most prominent point of the nose).
2) Pressure on the interface
We used an instrumented stretchable array from Pressure Profile Systems equipped with 16x16 pressure sensors, which have a resolution of 1cm and an active area of 160x160 mm to measure pressure distribution between head and helmet. The head was divided in 5 regions in order to map the pressure interaction of the whole head.
3) Subjective asssesment
The 10 subjects tried on the 3 sizes of two helmets (sport and executive). When a helmet was so small that it was impossible to be put on (usually on size S) the trial was neglected. While wearing the helmet, users answered a questionnaire about fitting perception and preference focusing on the five cranial regions. The global comfort perception was also rated by the subjects in a scale ranging from 1 to 7 (table 1).
Table 1. Rating scale to assess subjective comfort.
Which are the relevant anthropometric measures to design helmets?
1) Influence of head anthropometry on pressure pattern
Significant correlations between anthropometry and pressure on the frontal region (region 2) were obtained. Longer head breadth, length and perimeter entailed higher pressures in the frontal region.
Table 2. Significance of the ANOVA test comparing pressure on region 2 provided by both type of helmets on sizes M.
|Anthropometry of the head||ANOVA Significance|
2) Relationship between pressure patterns and users’ perception
Significant correlations between pressure and user ´s perception of fitting comfort were obtained on the antero-posterior axis, medio-lateral axis and cheeks. Lower pressures on these areas entailed lower level of perceived comfort (table 3). These results (an increase on pressure is related to an increase to fitting comfort) suggest that once you can wear a helmet you like it tightly attached.
Table 3. Correlation coefficients and level of significance between pressure in different areas and perceived comfort.
3) Relationship between head anthropometry and the geometric interference
The areas and volumes of the geometrical interference calculated from the virtual alignment of the 3D head scan and the 3D CAD model of the helmet were correlated with anthropometric measures of the head to analyze their consistency. Significant correlations were obtained between the volume of the interference in the top head area (region 1) and head breath, head length and head circumference for the executive helmet model (table 4).
Table 4. Correlation coefficients and level of significance between the volume of interference and anthropometric measures of the head for the executive helmet model.
Alemany, S., Olaso, J., Nacher, B., Gil, M., Hernández, A., Pizá, M., Solves, C.