7 research outputs found
Collection of anthropometry from older and physically impaired persons: traditional methods versus TC2 3-D body scanner
With advances in technology it is now possible to collect a wide range of anthropometric data, to a high degree of accuracy, using 3D light-based body scanners. This gives the potential to speed up the collection of anthropometric data for design purposes, to decrease processing time and data input required, and to reduce error due to inaccuracy of measurements taken using more traditional methods and equipment (anthropometer, stadiometer and sitting height table). However, when the data collection concerns older and/or physically impaired people there are serious issues for consideration when deciding on the best method to collect anthropometry. This paper discusses the issues arising when collecting data using both traditional methods of data collection and a first use by the experimental team of the TC2 3D body scanner, when faced with a ‘non-standard’ sample, during an EPSRC funded research project into issues surrounding transport usage by older and physically impaired people. Relevance to industry: Designing products, environments and services so that the increasing ageing population, as well as the physically impaired, can use them increases the potential market. To do this, up-to-date and relevant anthropometry is often needed. 3D light-based bodyscanners offer a potential fast way of obtaining this data, and this paper discusses some of the issues with using one scanner with older and disabled people
Analysing capture-recapture data when some variables of heterogeneous catchability are not collected or asked in all registrations
Registrations in epidemiological studies suer from incompleteness, thus a general consensus is to use capture–recapture models. Lately, there has been a thrust to incorporate covariates which relate to the capture probabilities in order to improve the estimate of population size. Current approaches utilize covariates observed in all the pertinent registrations. In epidemiological applications, one often encounters capture–recapture data where some covariates are measured by some but not by all of the registrations under scrutiny. In this article, the usefulness of these types of covariates is evaluated and furthermore a methodology for analysing such capture–recapture data is presented. The methodology is illustrated by applying it to data on neural tube defects in the Netherlands