This research aims to obtain more insight in the perception of fabric drape and how fabric drape can be cat-egorized With the current 3D virtual technologies to simulate garments the fashion and clothing industry can speed up work processes, improve accuracy and reduce material consumption in fit, design and sales. Although the interest in 3D technology is increasing, the implementation on a large scale emerges only slowly. At the threshold between physical and virtual fitting the fashion industry faces new challenges and demands re-quiring responses out of rule. The measurement of fabric drape started in the first half of the previous cen-tury, after the introduction of 3D garment simulation fabric drape gained interest from more researchers to obtain information for the virtual drape. Intensive research has been undertaken to define ‘fabric hand’, however, research is limited for the definition of fabric drape. Better understanding of how fabrics drape and how they can be selected based on their drape might contribute to the understanding of the virtually as-sessed material and accelerate the selection process of virtually, as well as digitally presented fabrics. For this research the drape coefficient of 13 fabrics, selected based on their drape, was measured with the Cusick drape tester. Images and videos of the fabrics draped on pedestals were presented to an expert tex-tile panel who were asked to define the fabric drape. From these definitions categories, as well as identifying key-words, were derived. During a group session the expert panel evaluated the drape categories and identi-fying key-words. In the next phase an expert user panel, familiar with the assessment of fabrics in a virtual environment, assessed the appropriateness of the categories and identifying key-words which were present-ed along with the fabric drape images and videos. Moreover, both panels judged the stiffness and amount of drape, next to that they indicated similar draping fabrics. The relation between the subjective assessment of drape and the drape coefficient was investigated. The agreement of the user panel with the drape categories defined and evaluated by the textile panel was high. Further, the agreement of the majority of the user panel with the identifying key-words was above 78%. A strong relation was found between the measured drape coefficient and the subjectively assessed stiffness and amount of drape. Additionally, the analysis of the fabrics combined by the panels based on drape simi-larity, as well as the analysis of the drape coefficients, confirms with previous research, that significantly dif-ferent fabrics can have a similar drape. Fabrics can be divided in drape categories based on the way they drape, and the identifying key-words are useful to distinguish between significantly different fabrics with similar fabric drape. Moreover, the cate-gories are related to the drape coefficient.
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Objective: To evaluate psychometrics of wearable devices measuring physical activity (PA) in ambulant children with gait abnormalities due to neuromuscular conditions. Data Sources: We searched PubMed, Embase, PsycINFO, CINAHL, and SPORTDiscus in March 2023. Study Selection: We included studies if (1) participants were ambulatory children (2-19y) with gait abnormalities, (2) reliability and validity were analyzed, and (3) peer-reviewed studies in the English language and full-text were available. We excluded studies of children with primarily visual conditions, behavioral diagnoses, or primarily cognitive disability. We performed independent screening and inclusion, data extraction, assessment of the data, and grading of results with 2 researchers. Data Extraction: Our report follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed methodological quality with Consensus-based Standards for the selection of health measurement instruments. We extracted data on reported reliability, measurement error, and validity. We performed meta-analyses for reliability and validity coefficient values. Data Synthesis: Of 6911 studies, we included 26 with 1064 participants for meta-analysis. Results showed that wearables measuring PA in children with abnormal gait have high to very high reliability (intraclass correlation coefficient [ICC]+, test-retest reliability=0.81; 95% confidence interval [CI], 0.74-0.89; I2=88.57%; ICC+, interdevice reliability=0.99; 95% CI, 0.98-0.99; I2=71.01%) and moderate to high validity in a standardized setting (r+, construct validity=0.63; 95% CI, 0.36-0.89; I2=99.97%; r+, criterion validity=0.68; 95% CI, 0.57-0.79; I2=98.70%; r+, criterion validity cutoff point based=0.69; 95% CI, 0.58-0.80; I2=87.02%). The methodological quality of all studies included in the meta-analysis was moderate. Conclusions: There was high to very high reliability and moderate to high validity for wearables measuring PA in children with abnormal gait, primarily due to neurological conditions. Clinicians should be aware that several moderating factors can influence an assessment.
