A framework for collecting inclusive design data for the UK population
Related Experiment Video
Updated: May 11, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Pat Langdon1, Daniel Johnson2, Felicia Huppert3
1Cambridge Engineering Design Centre, University of Cambridge, UK.
Abstract:
Successful inclusive product design requires knowledge about the capabilities, needs and aspirations of potential users and should cater for the different scenarios in which people will use products, systems and services. This should include: the individual at home; in the workplace; for businesses, and for products in these contexts. It needs to reflect the development of theory, tools and techniques as research moves on. And it must also to draw in wider psychological, social, and economic considerations in order to gain a more accurate understanding of users' interactions with products and technology. However, recent research suggests that although a number of national disability surveys have been carried out, no such knowledge currently exists as information to support the design of products, systems and services for heterogeneous users. This paper outlines the strategy behind specific inclusive design research that is aimed at creating the foundations for measuring inclusion in product designs. A key outcome of this future research will be specifying and operationalising capability, and psychological, social and economic context measures for inclusive design. This paper proposes a framework for capturing such information, describes an early pilot study, and makes recommendations for better practice.
Related Concept Videos
Data Collection by Survey
Data Collection I
Data Validation
Nursing assessment guides are generally based on holistic models rather than medical...
Data Collection II
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
