measuring biceps, triceps, subscapular and iliocristal
skinfolds.
The body density was estimated using the
equations of Durnin & Womersley (Durnin and
Womersley, 1974) and the %BF was estimated using
the equation of Siri (Siri, 1961). Table 3 presents the
statistical data corresponding to the respective
sample.
Table 3: Characterization of the sample (n =14)
a
.
Age (years) 21.36 ± 4.80
Height (m) 1.64 ± 1.33
Weight (kg) 59.60 ± 8.01
Original Harpenden BF (%) 27.94 ± 5.49
Adipsmeter BF (%) 28.26 ± 5.52
Adipsmeter - Harpenden (%) 0.31 ± 0.58
a
Mean values ± standard deviation.
A strong association between the values of the
%BF, calculated by the equation of Siri, with
skinfold measurement made with both the original
Harpenden skinfold calliper (%BF Harpenden) and
with the Adipsmeter (%BF Adipsmeter) was
achieved (r = 0.996). The slope of the regression line
is near the unit (0.999), corroborating the agreement
between these two variables, Figure 3.
y = 0,9994x + 0,3312
R
2
= 0,992
0,00
5,00
10,00
15,00
20,00
25,00
30,00
35,00
40,00
0,00 5,00 10,00 15,00 20,00 25,00 30,00 35,00 40,00
%BF Harpenden
%BF Adipsmeter
Figure 3: Percent body fat (%BF) measured by Harpenden
and by Adipsmeter linear relationship. (—) linear fit line.
In this study, the value of SEE (standard error of
the estimate) (0.58) is ideal according to the existing
bibliography indicating that SEE must be less than
3% for a new method to be accepted as accurate
(Lohman, 1996).
It is also reported in the literature that the total
error, TE, can be calculated as:
()
∑
−= nyyTE
HA
/
2
(1)
where y
H
and y
A
are the values measured by
Harpenden and Adipsmeter, respectively) is the best
parameter for evaluating differences between two
measures (Lohman, 1992). In our study, TE is 0.31,
indicating a very high level of agreement between
the measurements obtained by the two skinfold
callipers.
5 FINAL COMMENTS
The integrated system Adipsmeter, due to its
mechanical design, presents better technical
characteristics, namely an extended measurement
range, a near constant pressure between clamp
surfaces for the whole measurement range, better
handling and lighter weight. Its electronics provides
also a better resolution and a suitable wireless
protocol for health environments.
The automatic task procedure during
measurement significantly reduces evaluation
subjectivity and considerably increases the checking
task efficiency, offering graphical information of the
%BF individual level.
Nevertheless, new developments are now being
prepared for improving even further the novel
skinfold calliper performance. Since the rate and
resolution of the data transfer are suitable for studies
of tissue dynamics, the main idea is to explore the
dynamic response of subcutaneous tissues when
subject to a compression effect in order to better
characterize the body composition.
Furthermore it is within one of the main
objectives to take advantage of current techniques
such as artificial neural networks as well as the
Adipsmeter capabilities for developing new
algorithms for data processing (Barbosa et al.,
2010).
REFERENCES
Amaral, T., Restivo, M. T., Guerra, R., Marques, E.,
Chousal, M. F., Mota, J. (2010). Validation of a digital
skinfold system for estimating body fat based on
skinfold thickness measurement. Accepted to the
British Journal of Nutrition.
Barbosa, M. R., Amaral, T., Chouzal, M. F., Restivo, M.
T. (2010). Neural Networks Based Approach to
Estimate Body Fat (%BF). In Controlo2010, 7-10
September, Coimbra Portugal.
Durnin J. V., Womersley J. (1974). Body fat assessed
from total body density and its estimation from
skinfold thickness: measurements on 481 men and
women aged from 16 to 72 years. British Journal of
Nutrition; 32(1):77-97.
European Parliament. (2008). European Parliament
Resolution of 25 September 2008 on the White Paper
ADIPSMETER - A New Skinfold Calliper System
177