Comparison of Manual Anthropometry and a Mobile Digital

Anthropometric System

Anita Bušić

, Josip Bušić

, John Coleman

and Jožef Šimenko

Science Department, LIVE GOOD d.o.o., Technology Park Zagreb, Golikova 69, Zagreb, Croatia

Technology Department, LIVE GOOD d.o.o., Technology Park Zagreb, Golikova 69, Zagreb, Croatia

University of Essex, Colchester, U.K.

Keywords: Morphology, Anthropometry, Portable, Protocol.

Abstract: With the progress of technology, new digital shape-analysis tools are being developed for use in several

different fields. Innovation and market demand has pushed developers to create a portable 3D scanner. The

aim of this research was to perform a comparison of a new portable measuring system for digital measurement

of anthropometric dimensions of the body, with the system of manual anthropometry. The results show that

the Coefficient of determination (R2) was in 7 measurements over 90%, in 6 measurements over 80%, and in

2 measurements above 74.9%. Cronbach Alpha results of compared variables were all over 90%, which show

very strong expected correlations. No significant bias between measurement techniques was shown as Bland-

Altman plots showed a good agreement between measurement techniques with a small number of outliers.

Results provide high validity and accuracy of the new portable scanner when correctly used. However,

methods of 3D body scanning and classical anthropometry should not be regarded as interchangeable as there

are differences in initial body positions due to the implementation of measurement protocols. Further work is

recommended to make the two methods more interchangeable, with the possible usage of corrective

coefficients.

1 INTRODUCTION

With the progress of technology, new digital shape-

analysis tools are not limited to the traditional one-

dimensional measurements, but instead, they enable

measurement of complex geometrical features (i.e.,

curvatures and partial volumes) (Bragança et al.,

2014). With the advancement of the anthropometrical

field and application of 3D body scanners, methods

for obtaining anthropometric body data have become

more practical, contactless, fast and, above all,

accurate (Simmons & Istook, 2003; Zhang et al.,

2014; Ryder & Ball, 2012; Bragança et al., 2014).

These methods range from laser scanners to mobile

applications (Katović et al., 2016; Gruić et al., 2019).

The 3D scanning methods are frequently used in a

variety of fields as the textile industry (Apeagyei,

2010; Troynikov & Ashayeri, 2011), sport (Schranz

et al., 2010; Rauter, Vodičar & Šimenko, 2017;

Šimenko et al., 2017; Kambič et al., 2017), healthcare

https://orcid.org/0000-0002-0552-1492

https://orcid.org/0000-0002-7668-2365

(Treleaven & Wells, 2007; Sims et al., 2012), national

surveys of the general population (Wells et al., 2015),

motor performance (Lim et al., 2015; Sevick et al.,

2016; Taha et. al., 2016), posture/balance training

(Dutta et al., 2014; Mentiplay et al., 2013; Oh et al.,

2014; Saenz-deUrturi & Garcia-Zapirain Soto, 2016)

and rehabilitation (Galna et al., 2014; Mobini et al.,

2015; De Rosario et al., 2014; Shapi’i et al., 2015).

Advantages of 3D scanning represent a rapid raw data

collection, a wide variety of digital shape outputs that

can extend to 2D or 3D format, an electronic

achieving of scans, which could be utilized in future

analysis with improved software, a construction, and

comparison of composite shape models, etc. (Wells et

al., 2015; Šimenko & Čuk, 2016). The 3D body

scanning systems are in general stationery, but the

market demand for a portable 3D scanner has pushed

the developers to create new products. The validity of

instruments in clinical and sport application differ,

therefore the goal of this research was to initially

Buši

c, A., Buši

c, J., Coleman, J. and Šimenko, J.

Comparison of Manual Anthropometry and a Mobile Digital Anthropometric System.

DOI: 10.5220/0010178201090115

In Proceedings of the 8th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2020), pages 109-115

ISBN: 978-989-758-481-7

109

perform a comparison of the results acquired by a new

portable measuring system for digital measurement of

anthropometric dimensions of the body, with the

results of manual anthropometry.

2 METHODS

2.1 Subjects

This study included 51 subjects consisting of 12

females and 39 males. All of them participated

voluntarily and gave written consent.

2.2 Variables

Measurements were performed in the Physiological

Laboratory of the University of Ljubljana, Faculty of

Sport, Ljubljana, Slovenia. Anthropometrical

measurements in a classic setting were performed by

an expert with extensive measurement experience. 3D

measurement was conducted by an expert from the

Technology Department of LIVE GOOD d.o.o.,

Zagreb, Croatia.

2.2.1 Manual Anthropometry

Body height was measured with the GPM

anthropometer (Switzerland). Chest girth, breast

girth, hips girth, waist girth, Left (L) – Right (R)

upper arm girth, L - R elbow girth, L - R forearm

girth, L - R wrist girth, L - R upper leg girth, and L -

R lower leg girth were measured using a flexible and

inextensible tape with a 1 mm accuracy, as according

to guidelines by the International Biological Program

(IBP) (Lohman et al., 1988). Thus, IBP’s basic rules

and principles relating to the choice of parameters,

standard conditions, and measurement techniques

were followed.

2.2.2 Scanning Protocol

Subjects were scanned in a standing position with

legs 30 cm apart on a designated line. Arms were

elevated to a 90° angle, parallel to the ground, with

straight elbows. Subjects were standing in form-

fitting underwear. Scans of each subject were taken

twice.

Scanning was performed by going once around

the subject, with the iPad-Structure Sensor held

perpendicular to the ground, at approximately half of

the subject’s height. Space around the subject was

sufficient to take a full-body scan, optimally a 3 m

radius, although a 2 m radius is still sufficient. Room

was sufficiently illumined, with low levels of infrared

light. Time per scan was usually around 30 seconds.

2.2.3 Technical Specifications

Scanning hardware consisted of the Structure Sensor,

(Occipital, Inc., San Francisco, CA, USA) mounted

on an iPad Air 2 (Apple, Inc., Cupertino, CA, USA).

The minimum and maximum recommendations by

the manufacturer for a Structure Sensor is to scan

from 40 cm to 3.5 m, with the precision of 0.5 mm at

40 cm (0.15%) and 30 mm at 3 m (1%). Resolution of

the acquired frames is VGA (640 x 480) or QVGA

(320 x 240). The frame rate of scanning was 30 / 60

frames per second. Illumination consisted of an

infrared structured light projector with uniform

infrared LEDs. Scanner field of View horizontally

spans 58°, and vertically 45°.

The scanning software was part of a digital health

platform BodyRecog PRO that performed health risk

assessments for certain cardiovascular diseases, type

2 diabetes, and certain cancers based on 3D scan-

obtained body measurements (BodyRecog Metrics,

Inc., Boston, MA, USA). The software allowed for

manual adjustments of each girth position taken if

required. Saved 3D scan measurements were

automatically transferred to the cloud-based web app

for further analyses, i.e. health risk assessments.

2.3 Statistical Analysis

Analyses were conducted using SPSS for Windows

(Version 21.0; SPSS, Inc., Chicago, IL, USA). Data

were presented according to the descriptive statistics

(Means ± SD). Furthermore, we performed the

following tests: Kolmogorov-Smirnov test,

coefficient of variation (CV), standard error of

measurement (SEM), paired-sample T-test, Pearson

correlation, coefficient of determination (R

Cronbach’s Alpha, Bland-Altman (Bland & Altman,

1986) and average relative error. Relative error was

calculated as the absolute difference between the 3D

scanning method and classical anthropometry result

and divided with classical anthropometry result, and

at the end, the average relative error was calculated.

Bland-Altman method of assessing agreement (Bland

& Altman, 1986) was performed using the MedCalc

software (Version 14.8.1; MedCalc®, Belgium). For

calculating Bland-Altman figures, we subtracted

classical anthropometry values from the values

obtained by the 3D body scanning. All statistical

significances for t-test, Pearson correlation and

Cronbach’s alpha were set to p<0.05.

icSPORTS 2020 - 8th International Conference on Sport Sciences Research and Technology Support

110

3 RESULTS AND DISCUSSION

Table 1 presents the acquired results reflecting strong

Pearson correlation coefficient values. Larger

differences were detected in the breast and chest girth,

but this reliability issue can be explained by the fact

that the chest is always in slight movement due to

breathing. The same issue also occurs in breast and

chest girth measurements in manual anthropometry.

Also, the difference in the data acquisition line exists

in those measurements. The manual anthropometry

(measurement tape) in those measurements do not all

the time firmly touch the skin due to the anatomical

structure of bones (angle of the scapula, sternum and

backbone) and certain width of the tape. However, the

mobile 3D body scanner acquires data from the

contours of the body-skin regardless of angles and

does not measure a straight line, but the entire length

of the contours in acquired 2D cross-sections. This is

evident in the fact that 3D-acquired values in those

two measurements are larger than the manual

anthropometry values, which confirms and explains

the differences. SEM between the two techniques is

pretty much the same, which means both techniques

were performing with a fairly similar error.

Coefficient of determination (R

) shows that in 7

measurements it amounts to over 90%, in 6

measurements to over 80%, and in 2 measurements

Table 1: Descriptive statistics, Standard error (SE), Coefficient of variation (CV), Standard error of measurement (SEM),

Pearson correlation, Coefficient of determination (R

), Mean difference, T-test significance, Cronbach’s Alpha and Average

relative error.

Mean SD SE CV SEM

Pearson

corr.

Mean

Diff.

Sig.

T-test

Cronb.

Alpha

Aver.

Rel. err.

Pair 1

Body Height A 179.16 9.12 1.665 5.090 0.499

0.995 0.990 0.961 0.007 0.997 0.004

Body Height 3D 178.65 9.41 1.717 5.265 0.515

Pair 2

Waist Girth A 76.66 5.41 0.988 7.057 0.593

0.976 0.953 1.216 0.000 0.988 0.023

Waist Girth 3D 78.35 5.60 1.022 7.145 0.613

Pair 3

Hips Girth A 97.67 4.20 0.766 4.295 0.849

0.922 0.849 1.664 0.000 0.959 0.015

Hips Girth 3D 99.04 4.20 0.767 4.243 0.851

Pair 4

Chest Girth A 95.64 8.27 1.510 8.647 1.547

0.937 0.878 2.898 0.000 0.965 0.044

Chest Girth 3D 99.57 7.49 1.367 7.520 1.401

Pair 5

Breast Girth A 94.08 7.17 1.310 7.624 0.907

0.969 0.939 1.805 0.052 0.984 0.017

Breast Girth 3D 94.75 7.29 1.330 7.689 0.922

Pair 6

Right Upper Arm Girth A 27.98 2.85 0.520 10.178 0.493

0.942 0.887 0.977 0.000 0.970 0.048

Right Upper Arm Girth

29.26 2.87 0.523 9.797 0.496

Pair 7

Left Upper Arm Girth A 27.21 2.70 0.492 9.911 0.409

0.959 0.919 0.851 0.000 0.977 0.053

Left Upper Arm Girth 3D 28.66 2.95 0.539 10.291 0.447

Pair 8

Right Forearm Girth A 27.00 2.44 0.446 9.050 0.328

0.965 0.931 0.673 0.000 0.982 0.024

Right Forearm Girth 3D 26.51 2.55 0.465 9.611 0.342

Pair 9

Left Forearm Girth A 26.40 2.52 0.461 9.559 0.299

0.972 0.945 0.592 0.001 0.986 0.021

Left Forearm Girth 3D 26.00 2.43 0.443 9.337 0.287

Pair 10

Right Wrist Girth A 17.02 1.33 0.242 7.789 0.293

0.910 0.829 0.599 0.767 0.951 0.026

Right Wrist Girth 3D 17.05 1.45 0.264 8.479 0.320

Pair 11

Left Wrist Girth A 16.86 1.28 0.234 7.589 0.311

0.889 0.789 0.611 0.468 0.941 0.026

Left Wrist Girth 3D 16.78 1.30 0.238 7.769 0.317

Pair 12

Right Upper Leg Girth A 54.46 3.61 0.658 6.620 0.614

0.948 0.898 1.163 0.034 0.971 0.018

Right Upper Leg Girth

53.99 3.27 0.596 6.050 0.556

Pair 13

Left Upper Leg Girth A 53.65 3.50 0.638 6.514 0.399

0.977 0.954 0.820 0.073 0.987 0.012

Left Upper Leg Girth 3D 53.38 3.75 0.685 7.032 0.428

Pair 14

Right Lower Leg Girth A 37.17 2.37 0.432 6.366 0.639

0.865 0.749 1.196 0.073 0.927 0.024

Right Lower Leg Girth

36.86 2.19 0.401 5.954 0.593

Pair 15

Left Lower Leg Girth A 37.20 2.38 0.434 6.389 0.537

0.912 0.833 1.134 0.939 0.949 0.022

Left Lower Leg Girth 3D 37.22 2.75 0.502 7.390 0.621

3D - measurements obtained with the portable 3D scanner, A - measurements obtained with classical anthropometry

Comparison of Manual Anthropometry and a Mobile Digital Anthropometric System

111

above 74.9%. These results are acceptable. Results of

Cronbach Alpha are over 90%, which indicates very

strong expected correlations.

The biggest differences in average relative error

were in chest measurements 4.4% (which is

understandable due to reasons explained before in

SEM) and upper arm girth (5.3% for the left and 4.8%

for the right arm). Differences in the upper arm girths

can be explained by the possibility of arms being fully

extended in the elbow joint. The difference can occur

when the subject fully elicits the elbow (in some more

flexible subjects even hyperextension can occur), and

thus triggers the triceps (consequently the triceps is

larger and biceps is more extended), and when the

subject relaxes its arms smoothly and does not

activate the triceps fully (consequently the triceps is

smaller). Also, the position with arms elevated to the

90° angle can cause minor fluctuation of arm

positions, which can lead to larger differences. All

other measurements’ error is below 2.8%, which

presents a good and excitable result.

Figure 1, Figure 2 and Figure 3 present Bland-

Altman plots, for all critical parameters showing a

good agreement between measurement techniques.

Figure 1: Bland-Altman plots for the body height, chest girth, breast girth, waist girth and hips girth.

160 170 180 190 200

-3

-2

-1

Mean of BodyHeight_A and BodyHeight_3D

BodyHeight_A - BodyHeight_3D

Mean

0,5

-1.96 SD

-1,4

+1.96 SD

2,4

80 90 100 110 120

-12

-10

-8

-6

-4

-2

Mean of ChestGirth_A and ChestGirth_3D

Chest Girth_A - ChestGirth_3D

Mean

-3,9

-1.96 SD

-9,6

+1.96 SD

1,8

80 85 90 95 100 105 110 115 120

-5

-4

-3

-2

-1

Mean of BreastGirth_A and BreastGirth_3D

BreastGirth_A - BreastGirth_3D

Mean

-0,7

-1.96 SD

-4,2

+1.96 SD

2,9

65 70 75 80 85 90

-5

-4

-3

-2

-1

Mean of WaistGirth_A and WaistGirth_3D

WaistGirth_A - WaistGirth_3D

Mean

-1,7

-1.96 SD

-4,1

+1.96 SD

0,7

90 95 100 105 110 115

-7

-6

-5

-4

-3

-2

-1

Mean of HipsGirth_A and HipsGirth_3D

HipsGirth_A - HipsGirth_3D

Mean

-1,4

-1.96 SD

-4,6

+1.96 SD

1,9

icSPORTS 2020 - 8th International Conference on Sport Sciences Research and Technology Support

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No significant bias between measurement techniques

was shown as Bland-Altman plots showed a good

agreement between measurement techniques with a

small number of outliers.

4 CONCLUSIONS

Altogether, the BodyRecog

mobile 3D scanner has

a great potential for anthropometric measurements

that may be used in a wide variety of fields from elite

sport, recreation, fitness to healthcare. The

comparison between the 3D scanning technology and

manual anthropometry shows a high agreement

between methods. It provides high validity and

Figure 2: Bland-Altman plots for the L and R upper arm girth, L and R forearm girth and for the L and R wrist girth.

24 26 28 30 32 34 36 38

-4,0

-3,5

-3,0

-2,5

-2,0

-1,5

-1,0

-0,5

0,0

0,5

1,0

Mean of RightUpperArmGirth_A and RightUpperArmGirth_3D

RightUpperArmGirth_A - RightUpperArmGirth_3D

Mean

-1,28

-1.96 SD

-3,19

+1.96 SD

0,63

30 35 40 45 50

-32

-30

-28

-26

-24

-22

-20

Mean of LeftUpperArmGirth_A and LeftUpperLegGirth_3D

LeftUpperArmGirth_A - LeftUpperLegGirth_3D

Mean

-26,2

-1.96 SD

-30,1

+1.96 SD

-22,2

22 24 26 28 30 32 34

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Mean of RightForearmGirth_A and RightForearmGirth_3D

RightForearmGirth_A - RightForearmGirth_3D

Mean

0,49

-1.96 SD

-0,82

+1.96 SD

1,81

20 22 24 26 28 30 32

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Mean of LeftForearmGirth_A and LeftForearmGirth_3D

LeftForearmGirth_A - LeftForearmGirth_3D

Mean

0,40

-1.96 SD

-0,76

+1.96 SD

1,56

Comparison of Manual Anthropometry and a Mobile Digital Anthropometric System

113

Figure 3: Bland-Altman plots for the L and R upper leg girth and for the L and R lower leg girth.

accuracy when correctly used. However, methods of

the 3D body scanning and classical anthropometry

should not be regarded as interchangeable as there are

differences in initial body positions due to the

implementation of measurement protocols (Wells et

al., 2015). Further work is recommended to make the

two methods more interchangeable, with the possible

usage of corrective coefficients.

ACKNOWLEDGEMENTS

The LIVE GOOD team would like to acknowledge

the great contribution of Prof.Dr.Sc. Marjeta Mišigoj-

Duraković in creating and testing various versions of

the BodyRecog PRO digital health platform. Without

her expert advice, we would not have achieved as

much as we did. Her team of the Laboratory of

Kinanthropometry at the Faculty of Kinesiology,

University of Zagreb, Croatia, has been exceptionally

cooperative and kind to us, and it has been a great

honour to work with them all.

We would also like to extend our gratitude to

Prof.Dr.Sc. Vladimir Medved who allowed us to use

his Laboratory of Biomechanics, Faculty of

Kinesiology, University of Zagreb, Croatia, as a

testing lab. His insight into technical matters has been

invaluable. Much gratitude goes to the Laboratory of

Biomechanics team, with a special mention of Dr.Sc.

Igor Gruić who has been an avid supporter of our joint

work, and Dr.Sc. Darko Katović whose statistical

abilities and knowledge of scientific validation

protocol has proven a truly great asset.

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