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Three-dimensional (3D) body scanners have the potential to evaluate changes to the human form through different clothing configurations, the use of protective equipment, or the effects of medical interventions. To achieve this, scans of an individual need to be superimposed for each experimental condition. The literature highlights that one of the limiting factors is postural variability. This paper describes a newly developed 'positioning aid' that stabilises the posture during the scanning process and is invisible on scans. The results of a study evaluating the efficacy of the positioning aid showed that it reduces postural variability for all body parts in lateral and longitudinal directions. A reference test with a rigid mannequin indicated that the 'technical' variability due to the scanner hardware and software significantly contributes to the residual variability. Furthermore, the study showed that the newly developed positioning aid overall increased the precision of the software-assisted extraction of body dimensions. [ABSTRACT FROM AUTHOR]

Recent evidence suggests that musculoskeletal disorders (MSDs) may be the result of a fatigue failure process in affected tissues. This paper describes a new low back exposure assessment tool (the Lifting Fatigue Failure Tool [LiFFT]), which estimates a "daily dose" of cumulative loading on the low back using fatigue failure principles. Only three variables are necessary to derive the cumulative load associated with a lifting task: the weight of the load, the maximum horizontal distance from the spine to the load, and the number of repetitions for tasks performed during the workday. The new tool was validated using two existing epidemiological databases: the Lumbar Motion Monitor (LMM) database, and a database from a U.S. automotive manufacturer. The LiFFT cumulative damage metric explained 92% of the deviance in low back disorders (LBDs) in the LMM database and 72-95% of the deviance in low back outcomes in the automotive database (depending on the outcome measure). Thus, LiFFT is practitioner friendly and its cumulative damage metric highly related to low back outcomes. [ABSTRACT FROM AUTHOR]

Helmet safety benefits are reduced if the headgear is poorly fitted on the wearer's head. At present, there are no industry standards available to assess objectively how a specific protective helmet fits a particular person. A proper fit is typically defined as a small and uniform distance between the helmet liner and the wearer's head shape, with a broad coverage of the head area. This paper presents a novel method to investigate and compare fitting accuracy of helmets based on 3D anthropometry, reverse engineering techniques and computational analysis. The Helmet Fit Index (HFI) that provides a fit score on a scale from 0 (excessively poor fit) to 100 (perfect fit) was compared with subjective fit assessments of surveyed cyclists. Results in this study showed that quantitative (HFI) and qualitative (participants' feelings) data were related when comparing three commercially available bicycle helmets. Findings also demonstrated that females and Asian people have lower fit scores than males and Caucasians, respectively. The HFI could provide detailed understanding of helmet efficiency regarding fit and could be used during helmet design and development phases. [ABSTRACT FROM AUTHOR]