Comparison of Manual Anthropometry and a Mobile Digital
Anthropometric System
Anita Bušić
1a
, Josip Bušić
2
, John Coleman
2
and Jožef Šimenko
3b
1
Science Department, LIVE GOOD d.o.o., Technology Park Zagreb, Golikova 69, Zagreb, Croatia
2
Technology Department, LIVE GOOD d.o.o., Technology Park Zagreb, Golikova 69, Zagreb, Croatia
3
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
a
https://orcid.org/0000-0002-0552-1492
b
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
Copyright
c
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
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
2
),
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
2
) 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
2
), Mean difference, T-test significance, Cronbach’s Alpha and Average
relative error.
Mean SD SE CV SEM
Pearson
corr.
R
2
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
3D
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
3D
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
3D
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
0
1
2
3
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
0
2
4
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
0
1
2
3
4
5
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
0
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
0
1
2
3
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
112
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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