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Identification and comparison of analogous parameters from three-dimensional anthropometric scanner for aviation applications
*Corresponding author: Shruthi B. Chandran, Institute of Aerospace Medicine, Bengaluru, Karnataka, India. dr.shruchand@gmail.com
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Received: ,
Accepted: ,
How to cite this article: Chandran SB, Sharma V, Binu Sekhar M, Nayak S, Raghunandan V. Identification and comparison of analogous parameters from three-dimensional anthropometric scanner for aviation applications. Indian J Aerosp Med 2025;69:9-18. doi: 10.25259/IJASM_19_2024
Abstract
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.
Keywords
Anthropometry
Ergonomics
Three-dimensional laser
Whole-body scanner
INTRODUCTION
Digital anthropometry has already replaced manual methods in various fields such as apparel, sports, and military, as the technology continues to evolve rapidly. Digitally obtained anthropometric data are generally considered more accurate. In addition, it significantly speeds up the data collection process by reducing the time required for data entry and processing, while also minimizing the risk of measurement errors. Numerous studies in both military and civilian contexts have focused on anthropometry, with most relying on digital techniques.[1-4]
Digital anthropometry has evolved from its early form, such as the Loughborough anthropometric shadow scanner,[5] to a range of modern technologies including laser line scanning, millimeter wave imaging, and time-of-flight scanning.[6] Among these, laser scanning is regarded as particularly accurate and precise,[6] facilitating the easy creation of detailed geometries. Nonetheless, most of today’s laser scanners have established protocols and standards tailored to non-aviation sectors such as sports, apparel, and related industries.[7] In India, however, anthropometric data relevant to aviation is still largely collected using manual methods. Many of the cut-off limits for aviation related criteria in the Indian military such as 5th to 95th percentile range for clothing fitment continue to be based on these traditional approaches. Given the advancements in technology and successful adoption in sectors such as sports and apparel, it is high time for India’s aviation sector to transit from manual to digital methods for anthropometric data collection. In the Indian context, transitioning from manual to digital anthropometry is essential, given the advantage digital technology offers over traditional methods. To support this shift, the Indian Air Force has acquired a VITUS three-dimensional (3D) whole-body scanner.
However, this scanner is not yet customized for aviation-specific applications. Tailoring the system for aviation purposes would enhance its effectiveness by generating outputs aligned with the sector’s specific requirements. This can be achieved by analyzing the scanner’s existing protocols in comparison with manual anthropometric methods and by exploring the potential for future enhancements. Such customization would enable optimal use of the scanner and expand its applications to areas such as cockpit workspace design and the development of aircrew equipment assemblies.
Therefore, this study was conducted to determine whether scanner-derived measurements could be used to compute parameters analogous to those obtained manually and to assess the associated measurement errors relative to the manual benchmarks.
MATERIAL AND METHODS
Subjects
A total of 205 subjects (200 males and 05 females) participated in this study after a signed informed consent after explaining the protocol which was approved by the Institute’s ethics committee in agreement with Helsinki’s principles. The subjects’ ages ranged between 18 and 50 years. Exclusion criteria included all individuals with musculoskeletal deformities or those who had any crash-landing or post-ejection disabilities. Body-fit laser-compatible clothing and tight-fitting head caps were worn by the subjects during scanning.
Materials
Institute of Aerospace Medicine (IAM) portable manual anthropometer, according to the design approved by AFMRC 1767/89, was used for manual measurements. VITUS 3D whole-body scanner [Figure 1] was used for scanning where the hardware is made by Vitronic (Vitronic Dr.-Ing. Stein, Bildverarbeitungssysteme GmbH, Hasengartenstr. 14, 65189 Wiesbaden, Germany) and the Anthroscan software is made by Avalution (Avalution GmbH, Europaallee 10, 67657 Kaiserslautern, Germany). This software has got an inbuilt algorithm to locate the necessary landmarks and compute the required parameters. These parameters obtained directly by the scanner are named automatic parameters. The software measures 152 automatic parameters. The VITUS 3D whole-body scanner consists of 04 sensor units (consisting of laser and a camera) one in each of the four corners of the scanner. This unit moves down during scanning, while projecting a laser line on the body of the subject, thus capturing the entire surface area of the surface to be measured. The various contours that are produced by the laser light emitted by the laser diode and read by the matrix camera inside the unit are transferred to a common coordinate system and recreates the digital image of the surface scanned. This image is displayed onto the operator PC for further functions.[8] In the VITUS 3D whole-body scanner used here, optical triangulation method is used that creates a “virtual twin” of the body scanned and its point cloud is used to generate a variety of anthropometric metrics, including the body surface area, through biometric analysis. The VITUS ANTHROSCAN body scanner software automatically calculates implemented anthropometric measurements based on DIN EN ISO 20685 standards with the option to make manual modifications. The scanning image is visually inspected to perform a quality check. The complete scanning procedure takes around 10 s.[8]
- VITUS 3D whole-body scanner.
Experimental protocol
The measurements were taken between 0800 and 1200 h in the Department of Human Engineering, at IAM, Bengaluru. A total of 57 parameters could be obtained through manual anthropometer; out of this, 30-aviation-related parameters were studied. In the 3D whole-body scanner, the standard manufacturer-defined standing posture was used for scanning. The subject stands upright on the footprints provided inside the scanner, with head level and looking straight ahead. Hands are made into fist, and arms are separated from the body at an angle [Figure 2]. During the scan, the subject takes a deep breath and holds till the scanning is complete [Figure 3]. All the subjects underwent manual measurements initially followed by the scanner measurements [Figure 4].
- Institute of Aerospace Medicine. Standard posture.
- Scanned image of Institute of Aerospace Medicine standard posture.
- Window showing automatic parameter measurements.
Data analysis
Out of the list of 152 automatic parameters, a subset of 09 parameters was identified which could be combined (added/ subtracted) to produce analogous parameters corresponding to 15 out of the 30 manual parameters of interest. The remaining 14 parameters (excluding weight) did not have any corresponding analogous scanner parameter from the list of 152 automatic parameters and were excluded from the study henceforth. An error analysis was carried out to compare the manual and analogous parameter measurement for the 205 subjects by measuring the relative percentage error. A correlation analysis and Bland-Altman analysis were carried out between the manual and analogous parameters. Next, a regression analysis was carried out to derive the “correction factor” required to be applied to the scanner data to reduce the error between manual and analogous parameters. The reduction in the difference of means of manual and scanner parameters after applying the correction factor was also compared. Further, the correlation and consistency between manual and analogous parameters pre- and post-correction were also compared. Parameters were compared using t-test for the significance of difference of the errors between the two methods, and Pearson correlation coefficient for correlation and Bland-Altman analysis for checking consistency among the manual and analogous parameters were used. Table 1 shows the list of manual and analogous anthropometric parameters.
| S. No. | Manual parameter | Corresponding analogous parameter |
|---|---|---|
| 1. | Weight | Weight |
| 2. | Height | Body height |
| 3. | Sitting height | Distance neck to buttock+ head height |
| 4. | Eyelevel height (erect) | Distance neck to buttock+ head height |
| 5. | Eyelevel height (relaxed) | Distance neck to buttock+ head height |
| 6. | Mid shoulder height | Distance neck to buttock |
| 7. | Acromion shoulder height | Distance neck to buttock |
| 8. | Thigh clearance height | NIL |
| 9. | Elbow rest height | NIL |
| 10. | Elbow reach fingertip | NIL |
| 11. | Elbow reach knuckle | NIL |
| 12. | Arm reach fingertip | Arm length |
| 13. | Arm reach knuckle | NIL |
| 14. | Functional arm reach (normal) | NIL |
| 15. | Functional arm reach (extended) | NIL |
| 16. | Shoulder width | Cross shoulder |
| 17. | Forearm to forearm width | NIL |
| 18. | Hip width | NIL |
| 19. | Buttock popliteal length | Buttock height – Knee height |
| 20. | Buttock knee length | Buttock height – Knee height |
| 21. | Knee height | Knee height |
| 22. | Functional leg length (horizontal) | Waist height |
| 23. | Buttock heel length (leg length) | Waist height |
| 24. | Chest circumference (expiration) | Bust/chest girth |
| 25. | Chest circumference (inspiration) | Bust/chest girth |
| 26. | Palm length | NIL |
| 27. | Palm breadth (with thumb) | NIL |
| 28. | Palm breadth (without thumb) | NIL |
| 29. | Foot length | NIL |
| 30. | Foot width | NIL |
RESULTS
Total subjects who participated in this study were 205 and the average age of the subjects was found to be 32.1 ± 10.8 years. After finding equivalent analogous parameters from automatic and manual list of parameters, the mean, standard error SD, and error for each of the manual and automatic parameters were found.
The correlation analysis between the manual and analogous parameters showed moderate to high correlation values ranging from 0.58 to 0.98. The correlation analysis is shown in Table 2. Next, a Bland-Altman analysis was carried out to derive the limits of agreement (LOA) corresponding to the 95% confidence interval for differences between the manual and the automatic analogous parameters. The plots are shown in Graphs 1-15. Further, a regression analysis was carried out which showed a linear relationship between the manual and analogous automatic parameters. A linear best fit was used to derive the correction factors to be applied to the analogous automatic parameters. After calculating the error between the manual and analogous parameters (percentage error calculated for each subject was normally distributed), correction factor obtained through regression analysis was applied to the analogous automatic parameters and corrected mean and SD were found. The mean absolute percentage error (MAPE) after application of correction factor was found and is shown in in Table 3. Graphs 1-15 show Bland Altman plots with the related Limits of Agreement (LOA) corresponding to the 95% confidence intervals.
| Manual parameter | Analogous parameter | Correlation |
|---|---|---|
| Height | Body height | 0.98 |
| Sitting height | Distance neck to buttock + Head height | 0.85 |
| Eyelevel height (erect) | Distance neck to buttock + Head height | 0.75 |
| Eyelevel height (relaxed) | Distance neck to buttock + Head height | 0.77 |
| Mid shoulder height | Distance neck to buttock | 0.73 |
| Acromion shoulder height | Distance neck to buttock | 0.70 |
| Buttock popliteal length | Buttock height – Knee height | 0.74 |
| Arm reach fingertip | Arm length | 0.64 |
| Shoulder width | Cross shoulder | 0.58 |
| Buttock knee length | Buttock height – Knee height | 0.78 |
| Knee height | Knee height | 0.83 |
| Functional leg length (horizontal) | Waist height | 0.92 |
| Buttock heel length (leg length) | Waist height | 0.89 |
| Chest circumference (expiration) | Bust/chest girth | 0.88 |
| Chest circumference (inspiration) | Bust/chest girth | 0.87 |
| Manual parameter (cm) | Mean±SD of manual parameters (cm) | Analogous automatic parameter | Mean±SD of automatic parameters (cm) | Error (%) | Correction fac (a × analogous)+b |
|---|---|---|---|---|---|
| Height | 170.6±6.0 | Body height | 170.0±6.2 | 0.54 | a=0.9651, b=6.5128 |
| Sitting height | 89.8±3.2 | Distance neck to buttock+Head height | 83.313.3 | 5.21 | a=0.7588, b=26.582 |
| Eyelevel height (erect) | 79.4±3.2 | Distance neck to buttock+Head height | 83.3±3.3 | 4.99 | a=0.7108, b=20.125 |
| Eyelevel height (relaxed) | 79.1±3.1 | Distance neck to buttock+Head height | 83.3±3.3 | 5.50 | a=0.7126, b=19.732 |
| Mid shoulder height | 63.8±2.3 | Distance neck to buttock | 59.1±2.8 | 7.48 | a=0.6013, b=28.266 |
| Acromion shoulder height | 61.6±2.3 | Distance neck to buttock | 59.1±2.8 | 4.47 | a=0.5756, b=27.567 |
| Buttock popliteal length | 47.2±2.5 | Buttock height – Knee height | 40.5±2.0 | 14.11 | a=0.9315, b=9.4645 |
| Arm reach fingertip | 83.7±3.6 | Arm length | 58.6±6.8 | 29.6 | a=0.6751, b=43.144 |
| Shoulder width | 43.8±2.2 | Cross shoulder | 46.8±2.6 | 7.29 | a=0.5090, b=20.031 |
| Buttock knee length | 57.6±2.8 | Buttock height – Knee height | 35.2±2.8 | 38.8 | a=1.0879, b=13.559 |
| Knee height | 54.1±2.4 | Knee height | 46.2±2.3 | 14.6 | a=0.8625, b=14.216 |
| Functional leg length (horizontal) | 74.8±5.0 | Waist height | 107.2±4.6 | 43.59 | a=0.9964, b=32.005 |
| Buttock heel length (leg length) | 105.1±5.1 | Waist height | 107.2±4.6 | 2.47 | a=0.973, b=0.8826 |
| Chest circumference (expiration) | 89.6±6.5 | Bust/chest girth | 97.9±7.8 | 9.45 | a=0.7226, b=18.780 |
| Chest circumference (inspiration) | 94.9±6.1 | Bust/chest girth | 97.9±7.8 | 5.37 | a=0.6751, b=28.672 |
| Height | 170.6±6.0 | 0.41 | 0.7 | ±2.1 | |
| Sitting height | 89.8±2.5 | 1.35 | 1.2 | ±3.1 | |
| Eyelevel height (erect) | 79.3±2.4 | 2.03 | 1.6 | ±4.2 | |
| Eyelevel height (relaxed) | 84.8±2.6 | 1.96 | 1.5 | ±3.9 | |
| Mid shoulder height | 61.9±2.0 | 3.36 | 1.2 | ±3.1 | |
| Acromion shoulder height | 61.6±1.6 | 2.02 | 1.2 | ±3.2 | |
| Buttock popliteal length | 38.4±0.2 | 2.58 | 1.2 | ±3.3 | |
| Arm reach fingertip | 83.3±4.7 | 3.07 | 2.1 | ±5.4 | |
| Shoulder width | 43.8±1.3 | 3.2 | 1.4 | ±3.5 | |
| Buttock knee length | 57.6±1.4 | 3.3 | 1.3 | ±3.3 | |
| Knee height | 54.1±2.0 | 1.9 | 1.0 | ±2.6 | |
| Functional leg length (horizontal) | 74.8±4.6 | 2.2 | 1.6 | ±3.9 | |
| Buttock heel length (leg length) | 105.1±4.5 | 1.8 | 1.8 | ±4.6 | |
| Chest circumference (expiration) | 89.5±5.7 | 2.6 | 2.3 | ±6.1 | |
| Chest circumference (inspiration) | 94.8±5.3 | 2.5 | 2.4 | ±5.9 | |
SD: Standard deviation
- Standing height manual versus Body height corrected.
- Sitting height erect manual versus Distance neck-buttock+head height corrected.
- Acromion shoulder height manual versus Distance neck-buttock corrected.
- Mid shoulder height manual versus Distance neck-buttock corrected.
- Eye height manual versus Distance neck-buttock+head height corrected.
- Eye height relaxed manual versus Distance neck-buttock+head height corrected.
- Functional leg length (horizontal) manual versus Waist height corrected.
- Knee height manual versus Knee height corrected.
- Buttock popliteal length versus Buttock height-knee height corrected.
- Leg length manual versus Waist height corrected.
- Shoulder width manual versus Cross shoulder corrected.
- Buttock knee length manual versus Buttock height-knee height corrected.
- Arm reach fingertip manual versus Arm length corrected.
- Chest circum (expiration) manual versus Chest girth corrected.
- Chest circum (inspiration) manual versus Chest girth corrected. values between analogous and manual parameters. The lowest
DISCUSSION
Aviation applications – such as cockpit design, aircrew equipment assembly, and related production processes – depend heavily on the anthropometric characteristics of the crew population. Anthropometry also plays a critical role in selecting aircrew members suited to the diverse cockpit configurations currently in use within India. Consequently, the aviation industry places a high emphasis on the accuracy of anthropometric data, as it forms the foundation of several key operations. Historically, anthropometric surveys relied on manual data collection, which was labor-intensive and required skilled personnel. At present, digital anthropometric technology is primarily designed for non-aviation industries.[9] Therefore, there is a need to standardize and validate its application within aviation-related sectors.
This study compares 30 aviation-relevant anthropometric parameters measured manually with those obtained digitally using a 3D body scanner. The scanner was capable of automatically computing 152 parameters. However, among the 30 manual parameters analyzed, only one – weight – had a directly equivalent measurement from the scanner. The remaining parameters could not be directly matched.
As a result, an effort was made to identify scanner-derived parameters that could serve as analogs to the manual measurements. A scanner parameter was considered analogous if it met two criteria: (1) Showing a moderate-to-high correlation with the corresponding manual measurement (Pearson’s correlation coefficient > 0.5) and (2) applying a correction factor to it resulted in a to it resulted in a low error (MAPE < 4%) when compared to the manual measurement.
Out of the 29 manual parameters (excluding weight which was direct equivalent from the scanner), only 15 parameters had corresponding analogous parameters. When the manual parameters were compared directly with their corresponding analogous parameters, moderate to high correlations were found between them, even though significant deviations existed between them due to differing measurement definitions. A regression analysis was applied, showing high R2 values were for the analogous parameters corresponding to Shoulder Width (R2 = 0.34), Arm Reach Fingertip (R2 = 0.42), and Acromion Shoulder Height (R2 = 0.49). All other parameters had a R2 value >0.5, when comparing the manual and analogous parameters. The difference between the manual measurements and corresponding analogous measurements could be reduced after applying the correction factor. It was seen that 1 parameter (standing height) had error <1%, 14 parameters (Sitting height, Eye level height (erect and relaxed), Mid shoulder height, Acromion shoulder height, Arm reach fingertip, Shoulder width, Buttock Popliteal length, Buttock knee length, Knee height, Functional leg length horizontal, Leg length, Chest circumference (inspiration and expiration) had error between 1% and 4%; and none had error >4%. A Bland-Altman analysis showed that the LOA for the 95% confidence interval ranged from ±2.1 cm to ±6.1 cm among the parameters.
This helps us to conclude that the corrected analogous automatic parameters from the digital method may be used in lieu of manual measurements where precision may be compromised for individual subjects while obtaining correct descriptive statistics, as in large-scale surveys. This may not be the case where precision is required over accuracy as in the case of research and development (R&D) of aircrew equipment development, devising new standard operating procedures (SOPs) for newer indigenous cockpit dimensions, etc. Logically, the number of comparable parameters that can be derived from a 3D scanner can be increased by incorporating additional landmarks and adopting postures that more closely align with the definitions of the required manual measurements. Furthermore, it is essential to validate the scanner’s landmark identification algorithm, particularly in relation to the morphological variations within the Indian population. Additional studies will be necessary to address these aspects in greater detail.
Recommendations
It was found that the use of analogous automatic parameters from the scanner to derive the manual parameters with required precision may not be possible from the scanner in the standard posture. Hence, it is recommended that instead of standard posture used for scanning, those similar to manual postures may be replicated in the 3D scanner and data may be computed using “user-assisted methods” to identify the landmarks from the scanned image to compute manual parameters from the scanner and their accuracy may be studied. If found accurate, automation for the identification of landmarks may be incorporated in the scanner software as well as additional postures may be introduced. Standardization and validation studies may be done for scanner-derived parameters for aviation applications from the automatically computed 152 parameters to explore the full potential of the 3D scanner as well.
CONCLUSION
This study attempted to determine the analogous scanner parameters corresponding to manual anthropometric parameters from the scanner parameters obtained through 3D whole-body scanner. Only 15 of the manual parameters under study had corresponding analogous parameter. These 15 analogous parameters could be constructed using a subset of 09 scanner parameters out of the total 152 parameters and were not obtained through a direct oneto-one relationship, but rather through the combination of multiple automatic parameters. After comparison of means and errors of the parameters from manual and digital methods, a correction factor obtained through regression analysis was applied. Although the percentage error between the means was reduced using correction factor, the analogous parameters could not be used as a potential replacement due to lack of consistency and agreement. The reason for this may be attributed to the difference in measurement definitions between automatic analogous and manual parameters. For example, the manually measured Buttock-Knee Length is not precisely equal to the analogous parameter of Buttock Height – Knee Height, even though they are highly correlated (Pearson’s correlation coefficient = 0.78). However, due to the proximate and highly correlated nature of the manual and automatic analogous parameters, it is possible to estimate the manual parameters from the scanner parameters with high accuracy, but not with high precision. The analysis of the study revealed that only a small number of scanner parameters could be reliably used in place of manual parameters with high precision.
Ethical approval:
The research/study approved by the Institutional Review Board at Institute of Aerospace Medicine, number IAM/ MD/07/2020, dated 19th February 2021.
Declaration of patient consent:
The authors certify that they have obtained all appropriate patient consent.
Conflicts of interest:
There are no conflicts of interest.
Use of artificial intelligence (AI)-assisted technology for manuscript preparation:
The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.
Financial support and sponsorship: Nil.
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