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Wrist motion provides an important metric for disease monitoring and occupational risk assessment. The collection of wrist kinematics in occupational or other real-world environments could augment traditional observational or video-analysis based assessment. We have developed a low-cost 3D printed wearable device, capable of being produced on consumer grade desktop 3D printers. Here we present a preliminary validation of the device against a gold standard optical motion capture system. Data were collected from 10 participants performing a static angle matching task while seated at a desk. The wearable device output was significantly correlated with the optical motion capture system yielding a coefficient of determination (R2) of 0.991 and 0.972 for flexion/extension (FE) and radial/ulnar deviation (RUD) respectively (p < 0.0001). Error was similarly low with a root mean squared error of 4.9° (FE) and 3.9° (RUD). Agreement between the two systems was quantified using Bland–Altman analysis, with bias and 95% limits of agreement of 3.1° ± 7.4° and −0.16° ± 7.7° for FE and RUD, respectively. These results compare favourably with current methods for occupational assessment, suggesting strong potential for field implementation.

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Clinicians and researchers have several approaches with which to assess eating disorder and related symptomatology, including interviews, self-report instruments, and behavioral measures. The purpose of this chapter is to describe a process, based on a functional approach, that will help assessors to develop assessments and choose instruments for eating disorders and eating-related problems. This approach takes into account both theoretical and practical concerns and allows assessors to individualize their assessments depending on their particular needs. This process starts with broad considerations about the context in which the assessment is to be given and ends with the choice of specific instruments to be used.

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