![](bg6.png)
previous studies. During STS, mean value of trunck
angle is between 18, 30
◦
and 49, 62
◦
, and in BTS, it is
between −3, 53
◦
and 54, 68
◦
.
The only parameter showing a main effect of the
factor ”condition” is the ratio in BTS transfer. For this
parameter, Kolmogorov-smirnov and Shapiro-Wilk
tests showed that the distribution follows a NORMAL
law (see Figure 6). Results from the one-way analy-
sis of variance (one-way ANOVA), whose factor is
condition, showed that there was a high variability in
the BTS ratio between normal condition and cognitive
condition (F(2, 27)= 4,2954, p= ,02401). A post hoc
within condition analysis was performed and showed
that there is a significant difference between normal
condition and cognitive condition, this last result is
very stimulating regarding the literature about dual
task paradigm field. In aging, the automatic motric-
ity seems less efficient and some functional activities,
as the TUG, need a cognitive involvement (Teasdale
and Simoneau, 2001). Some authors proposed that
the BTS motion could be an interesting tool to assess
posturo-motor abilities (Manckoundia et al., 2006) in
aged adults. Here we showed that a simple BTS anal-
ysis can reveal an impairment involved by the dual
task condition even in a population of young adults.
Figure 6: Result of one-way ANOVA analysis.
5 CONCLUSIONS
In this work, we have presented a novel movement
analysis system for real-time balance assessment in
the frail elderly. It captured and recorded the TUG
test movement using a Kinect sensor and nine spatio-
temporal parameters were automatically extracted for
sit-to-stand and back-to-sit transfers by 3D real-time
video processing. Obtained experiment results with
ten healthy young subjects showed good measure-
ment reliability and reproducibility with important
precision. In addition, we showed that even in young
healthy subjects, some modifications of motor pat-
terns can be seen in dual task condition. Moreover,
our system allows detecting some very fine changes
in posturo-motors abilities.
Our future works consist to perform TUG test for
real-time balance assessment in the frail elderly to
validate the proposed system in real world condition.
This study will open a new research and development
way for geriatric health which implies multiple as-
pects: user-friendly, hygiene, low-cost, home-based
environment, and automatic autonomy assessment.
REFERENCES
Bonnech
`
ere, B., Jansen, B., Salvia, P., Bouzahouene, H.,
Omelina, L., Cornelis, J., Rooze, M., and VAN
SINT JAN, S. (2012). What are the current limits of
the kinect sensor? Proc. 9th Intl Conf. Disability, Vir-
tual Reality & Associated Technologies (ICDVRAT),
pages 287–294.
Clark, R. A., Pua, Y.-H., Fortin, K., Ritchie, C., Webster,
K. E., Denehy, L., and Bryant, A. L. (2012). Valid-
ity of the microsoft kinect for assessment of postural
control. Gait & Posture, 36(3):372–377.
Gabel, M., Gilad-Bachrach, R., Renshaw, E., and Schuster,
A. (2012). Full body gait analysis with kinect. In 2012
Annual International Conference of the IEEE Engi-
neering in Medicine and Biology Society (EMBC),
pages 1964–1967.
Hagler, S., Austin, D., Hayes, T. L., Kaye, J., and Pavel, M.
(2010). Unobtrusive and ubiquitous in-home monitor-
ing: A methodology for continuous assessment of gait
velocity in elders. IEEE transactions on bio-medical
engineering, 57(4):813–820.
Mancini, M. and Horak, F. B. (2010). The relevance of clin-
ical balance assessment tools to differentiate balance
deficits. European journal of physical and rehabilita-
tion medicine, 46(2):239–248.
Manckoundia, P., Mourey, F., Pfitzenmeyer, P., and Pa-
paxanthis, C. (2006). Comparison of motor strate-
gies in sit-to-stand and back-to-sit motions between
healthy and alzheimer’s disease elderly subjects. Neu-
roscience, 137(2):385–392.
Stone, E. and Skubic, M. (2011). Evaluation of an inexpen-
sive depth camera for passive in-home fall risk assess-
ment. In 2011 5th International Conference on Perva-
sive Computing Technologies for Healthcare (Perva-
siveHealth), pages 71 –77.
Teasdale, N. and Simoneau, M. (2001). Attentional de-
mands for postural control: the effects of aging and
sensory reintegration. Gait & posture, 14(3):203–210.
Weiss, A., Hirshberg, D., and Black, M. (2011). Home 3D
body scans from noisy image and range data. In 2011
IEEE International Conference on Computer Vision
(ICCV), pages 1951–1958.
PreliminaryStudyontheDesignofaLow-costMovementAnalysisSystem-ReliabilityMeasurementofTimedUpandGo
Test
667