Identification and comparison of analogous parameters from three-dimensional anthropometric scanner for aviation applications

Objectives: This study aims to identify anthropometric parameters from a list of 152 automatically measured values generated by a three-dimensional (3D) laser whole-body scanner that closely corresponds to 30 aviation-related parameters traditionally measured manually. These scanner-derived parameters, obtained in a standing posture using the VITUS 3D whole-body scanner, are evaluated for their similarity and potential to replace the respective manual measurements Material and Methods: A total of 205 healthy human volunteers of age ranging from 18 to 50 years participated in this study. Institute of Aerospace Medicine (IAM) portable anthropometer and the standardized protocol used in the IAM were employed for manual measurements. Vitus 3D whole-body scanner with Anthroscan software was used as per the manufacturer-recommended protocol for 3D scanner measurements. Subjects underwent measurements in IAM Manual Anthropometric platform followed by 3D scanning in VITUS 3D whole-body scanner in the standard standing posture only. A total of 30 manual parameters measured using the IAM portable anthropometric platform were studied. The list of 152 scanner parameters, automatically measured, was explored for parameters identical to the 30 manual parameters having body region matching or closely related landmarks and measurement definitions. Out of the 30 manual parameters, only 15 (except weight) could be described in terms of analogous parameters derived using combinations of 09 scanner parameters taken from the list of 152 automatically measured scanner parameters. Here, analogous automatic parameters are defined as parameters that can be expressed as simple combinations of standard scanner parameters, that is, the analogous automatic parameters are derived parameters which are proximate to the manual parameters. For example, the manually measured buttock knee length is proximate (i.e., analogous) to the difference between the standard scanner parameters of “buttock height” and “knee height.” The differences in means of manual parameters and analogous automatic parameters were calculated and the mean difference of each comparable parameter was expressed as a percentage of average manual measurement. Next, the correlation between the manual and analogous automatic parameters was calculated and a regression analysis was carried out to derive the “correction factor” to be applied to the analogous automatic parameter to derive the corrected analogous parameter. The reduction in the difference between the means of manual and corrected analogous automatic parameters was also compared. Finally, a Bland-Altman analysis was carried out to measure the limits of agreement (LOA) between the manual and the corrected analogous parameters. Results: The correlation coefficient varied from 0.58 to 0.98 among the parameters. The percentage differences of means between the analogous and manual parameters ranged from 0.54% to 43.59 % on direct comparison which was brought down to 0.44–3.36% after applying the “correction factor.” In addition, the LOA within 95% confidence interval ranged from ±2.1 cm to ±6.1 cm among the parameters. Conclusion: It was discovered that the scanner may not be able to provide the necessary precision while in the standard posture when using analogous automatic parameters to generate the manual parameters. Therefore, it is advised that rather than using standard scanning postures, those that are similar to manual postures should be replicated in the 3D scanner. Manual parameters can then be computed from the scanner using “user-assisted methods” to identify landmarks from the scanned image, and their accuracy can be examined. If it is determined to be accurate, the scanner software may be upgraded to automatically identify landmarks and include more postures.