BJMB
Brazilian Journal of Motor Behavior
Special issue:
“Control of Gait and Posture: a tribute to Professor Lilian T. B.
Gobbi”
!
Rezende et al.
2023
VOL.17
N.4
150 of 157
Do timed up and go and five times sit to stand test outcomes correlate with trunk
stability? A pilot-study
LUCAS S. REZENDE
1
| PEDRO H. M. MONTEIRO
1
| JÚLIA A. OLIVEIRA
1
| CAROLINE R. SOUZA
1
| DANIEL B.
COELHO
2
| ALEXANDRE J. MARCORI
1
| LUIS A. TEIXEIRA
1
1
School of Physical Education and Sport, University of São Paulo, SP, Brazil
2
Federal University of ABC, São Bernardo do Campo, SP, Brazil
Correspondence to:!Pedro Henrique Martins Monteiro. Adress: Av. Professor Mello Moraes, 65 - Cidade Universitária, São Paulo, Brazil. Postal code: 05508-030.
email: pedromonteiro@usp.br
https://doi.org/10.20338/bjmb.v17i4.358
HIGHLIGHTS
• Dynamic balance stability was measured through
mediolateral trunk acceleration.
• Evaluation of clinical tests Five Times Sit-Stand (FTSS)
and Timed Up and Go (TUG).
• Evaluation of a new version of TUG requiring increased
dynamic balance stability.
• FTSS completion time correlated with trunk
accelerometry reflecting balance stability.
• TUG accelerometry seems to be more related to
movement speed than to body balance.
ABBREVIATIONS
FTSS Five Times Sit to Stand
ML Mediolateral
η
p
2
Partial eta squared
RMS Root mean square
r
p
Pearson's correlation
r
p
2
Squared correlation values
TUG Timed Up and Go
TUG
C
Conventional version of the test
TUG
DT
In addition to a dual task
TUG
OL
New overline version
PUBLICATION DATA
Received 12 04 2023
Accepted 09 06 2023
Published 20 06 2023
BACKGROUND: Five Times Sit to Stand (FTSS) and Timed Up and Go (TUG) are clinical
tests in which performance is evaluated through completion time, which can be thought to
reflect dynamic balance. Completion time in these tests, however, can be affected not only by
balance stability but also by other important components, such as legs’ muscular strength and
velocity.
AIM: This investigation aimed to evaluate the correlation of completion times in these clinical
tests and mediolateral (ML) balance stability measured through lower trunk accelerometry in
older individuals.
METHOD: Fifteen volunteers were evaluated, aged 60-86 years (M = 69.56±5.89 years). For
TUG, we evaluated the conventional version of the test (TUG
C
), in addition to a dual task
(TUG
DT
) and a new overline (TUG
OL
) version featured by increased balance demand. Balance
stability during test performance was measured through ML accelerations of the lower trunk.
RESULTS: The results indicated negative time-acceleration correlations for TUG
C
(r
p
= -.71,
r
p
2
=.50, p <.01) and TUG
DT
(r
p
= -.77, r
p
2
=.59, p <.01) and a positive correlation for FTSS (r
p
=.73, r
p
2
=.53, p <.01). The TUG
OL
test failed to show significant time-acceleration
correlations.
INTERPRETATION: Our results suggest that completion time in the FTSS test importantly
reflects dynamic balance stability in older individuals. On the other hand, ML trunk
acceleration when performing TUG seems to be more related to movement speed than body
balance. Our results suggest that completion time can be considered a predictor of dynamic
balance in the FTSS test.
KEYWORDS: Dynamic balance | Accelerometry | Aging | TUG | Five Times Sit to Stand
INTRODUCTION
The aging process leads to several consequences to the neuromuscular system, such as impoverished motor control and
reduced muscular strength, with implications for body balance
1
. Neural and muscular factors can limit the completion of whole-body skills
requiring dynamic balance in older individuals, such as getting up from a chair and walking
2
. Critically, reduced body balance stability
associated with aging can lead to falls
3
. A large percentage of falls involve instability in the mediolateral (ML) direction
4,5
, which is related
to the challenge of controlling the center of mass over a narrow support base as while walking
6
. Previous results have shown that step
width is increased in older individuals
7
and that ML displacement of the pelvis is a stronger predictor of falls than other gait variables
8
.
Assessing dynamic balance stability in the ML direction, then, can be considered particularly relevant for evaluating upright stability in
older individuals.
Some well-known tests for clinical evaluation requiring dynamic balance frequently applied to older individuals are Five Times
Sit-to-Stand (FTSS)
9,10
and Timed Up and Go (TUG)
11–13
. The FTSS consists of performing five repetitions of sitting on a chair and
standing up, completing the sequence as fast as possible. Performance is measured through time for test completion. Despite being a
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task constantly performed in everyday life, getting up from a chair is complex, requiring dynamic balance control, movement coordination
between the trunk and upper-lower limbs, and lower limb muscle strength
1,14,15
. Of particular interest as a tool for balance evaluation,
previous studies have shown that the FTSS is able to predict risk of recurrent falls
9
and to reveal balance disorders
16
. From these
findings, completion time in this test can be expected to be associated with measures of dynamic balance.
The TUG test requires the participant to get up from a chair, walking quickly toward a frontal target 3 m away on the floor,
circumvent the target (180 degrees turning), return to the chair and sit down. This is a straightforward mobility test
17,18
, but it has also
been described as a reliable clinical balance test
19
, having been suggested as a predictor of fall risk
8
. Further studies have shown that
during TUG performance, the addition of a secondary task (cognitive or motor) can increase the test's ability to discriminate fallers
13,20
.
Similar to the FTSS, this test has a limitation as a tool for direct measurement of dynamic balance, given that it can be assumed to be
affected by factors other than body balance, such as lower limb muscular strength and movement speed. In this regard, completion times
observed on performance of both FTSS and TUG can be thought to reflect relevant factors not directly related to dynamic balance.
Trunk accelerometry has been widely used for the assessment of balance control, both in quiet upright posture
21
and in
dynamic tasks
22–24
. Trunk acceleration indicates the rate of velocity change of the largest body segment, representing then a sensitive
measurement of trunk stability over time in static and dynamic balance tasks. By using a triaxial accelerometer, one can evaluate trunk
(balance) stability both the anteroposterior and mediolateral directions. This measuring tool that has been shown to be reliable and valid
for the evaluation of balance stability in healthy individuals
25
. Evaluation of trunk accelerometry through root mean square values has
been shown to be one of the most sensitive, reliable, and valid measurement of balance stability for healthy and neurological older
individuals
26
, indicating the central tendency of the acceleration magnitude. With an accelerometer attached to the lower trunk,
acceleration data expresses the magnitude of the trunk oscillation, serving as an index of postural stability, allowing for a direct and
accurate assessment of body balance. In different studies, accelerometry has been used to assess stability components in clinical tests
22–24,27
. However, there is a scarcity of tests in the literature objectively assessing dynamic balance in older individuals. In addition to
analyzing whether the already established tests actually correlate with balance through a direct measurement of trunk stability, a test that
more faithfully indicates dynamic balance is lacking in clinical evaluations. Since the tests currently employed in clinical research have
important extraneous components to balance affecting completion time, it becomes evident the relevance of understanding the extent to
which the completion time in the clinical tests TUG and FTSS is associated with direct measurements of balance stability during their
performance. Additionally, it is possible that a variation of TUG requiring increased body balance may be more discriminative of dynamic
balance than the conventional version in older participants. In this regard, walking on a narrow path has been shown to discriminate
between fallers and non-fallers in older individuals
28
. When used in association with trunk acceleration measurements, walking on a
straight line can provide useful information on balance stability in healthy older adults
29
. Measurement of trunk acceleration in the
mediolateral (ML) direction, in particular, can reflect the lateral trunk stability of the different components of the tests requiring chair
standing up and sitting (TUG and FTSS), in addition to walking straight forward and 180
°
body turning (TUG). All these test components
can be thought to be improved by having increased lateral trunk stability during their performance. From these findings, employment of a
narrow support base for the gait component of the TUG test, requiring walking on a straight line, might make the completion time more
representative of the balance component of this test
30
.
In the current investigation, we performed an exploratory pilot investigation in older individuals with the following primary aims:
(1) to evaluate the correlation of completion times observed in the FTSS and in different versions of the TUG test with a direct
measurement of trunk stability given by accelerometry while performing these tests; (2) to compare completion time and trunk stability of
a new version of the TUG test requiring increased dynamic balance with the versions being currently used of this test. As a secondary
aim, we evaluated the correlation between tests for both completion time and trunk acceleration to estimate the extent to which
performance in one test can predict performance in the others.
METHODS
Participants
Fifteen physically active individuals without history of falls, aged 60-86 years (M = 69.56±5.89 years), 5 men and 10 women,
participated in this study. All of them were contacted in programs for physical activity for seniors. The inclusion criteria were as follows:
ability to get up from a chair and walk unassistedly, and no reports of illness (e.g., neurologic), injury (e.g., orthopedic) or medication
consumption (e.g., muscle relaxant) that might affect performance in the applied tests. The single exclusion criterion was the inability to
perform one or more of the tests. The participants signed an informed consent form, which was approved by the local university ethics
committee.
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Test and equipment
In all tests, a sequence of movements was to be performed in the shortest time, with the interpretation that short completion
times indicate higher performance. Completion times were measured through a stopwatch, with visual detection of the onset and end of
each trial. The following tests were evaluated:
Five Times Sit to Stand (FTSS). The test was initiated with the participants sitting on a regular-sized chair (approximately 45 cm
high), without armrests, keeping their feet hip-width apart fully supported on the floor. The test consisted of getting up and sitting down
five times in the shortest time, refraining from discharging the whole body weight on the chair accent when sitting, while keeping their
arms crossed over the chest.
Timed Up and Go (TUG). For this test, three versions were analyzed. For the conventional version (TUG
C
), participants started
sitting on the chair, keeping both hands resting on the thighs and the feet hip-width apart fully supported on the floor. Following the
examiner's verbal prompt, participants were to stand up, walk as quickly as possible toward a cone positioned 3 m away on the ground in
front of the participant, circumvent the cone (180 degrees turning), return to the chair, turn and sit down
31
. The path was clear, flat and
without distractors. For the TUG dual-task version (TUG
DT
), participants performed the test as described for the conventional version
while simultaneously performing a cognitive task
13
. The cognitive component of this test consisted of speaking aloud names of colors,
fruits or animals throughout the test duration, according to the initial letter spoken by the examiner immediately before trial onset
32
. We
also analyzed a new version of the TUG requiring increased dynamic balance. In this version, participants were to perform the gait
component of the test by stepping during the whole gait over a 5-cm width straight line, marked through a tape on the floor. The cone
used in the other versions of this test was replaced by a transversal line crossing the end of the walking line. Participants were to cross
this line with one foot before returning, stepping over the line throughout their displacement. This test was named overline TUG (TUG
OL
).
This new version of the TUG test is proposed to pose a higher demand for ML balance by preventing participants from moving their feet
laterally during gait to increase ML body stability
7
. By introducing this modification to the TUG test, it is assumed that the completion time
is more representative of dynamic balance than the conventional and dual-task versions of this test. During the performance of all tests,
dynamic balance stability was evaluated through trunk acceleration in the ML direction. This measurement was made by using a triaxial
accelerometer (Delsys Trigno) attached to the lumbar region over the L3-L4 vertebrae of the trunk. Assessment of performance on the
TUG test based on an accelerometer attached to this body region has been shown to be effective in differentiating fallers and non-fallers
20
. To identify the start and end times of the trial, a manual electronic key was used. Recording of accelerometer signals was performed
using a Vicon system (Oxford, UK, Nexus 2.7).
Procedures
In all tests, a single familiarization trial was provided before the performance of three probing trials. In cases of failure to
perform a trial, it was replaced immediately. The sequence of tests was randomized across participants. Sitting rest intervals of 1 minute
between trials and 2 minutes between tests were provided to prevent fatigue. Data collection was completed in a single session of
approximately 40 minutes.
Accelerometer signals were sampled at a frequency of 1 kHz, and were recorded during the full duration of the tests. This
implies that for the three versions of the TUG test we did not differentiate the phases of standing up, walking, turning and sitting down.
After preliminary visual inspection of the signals, raw data were exported to a personal computer and processed offline by using MATLAB
routines (Mathworks, Natick, MA). Raw signals were amplified with a gain of 1000 and filtered through a 10 Hz fourth-order double pass
Butterworth filter.
Data analysis
Analysis was conducted for the total duration of each trial. Individual values were based on the average of the 3 probing trials
for each test. The following variables were analyzed: 1) time for test completion and 2) root mean square (RMS) of lower trunk
acceleration in the ML direction during the entire duration of the trial. Time for test completion was measured through a stopwatch
operated by a single examiner (LSR). We analyzed RMS acceleration in the ML direction, considering the visually determined whole time
duration of each trial (movement onset-end). Individual data were based on the average for three trials in each task. Acceleration data
were processed through a custom-written MATLAB software (MathWorks Inc., MA) routine.
Analysis of data distribution normality was performed through the Shapiro-Wilk test. Comparisons of completion time and trunk
acceleration between the three versions of the TUG test were made through one-way analyses of variance for repeated measures. Post
hoc comparisons were made through the Bonferroni test, with effect size indicated by partial eta squared (η
p
2
). The main statistical
analysis was performed through Pearson's correlation (r
p
) tests between completion time and RMS of lower trunk acceleration in the ML
direction for each test. In addition, we tested for the correlation of performance across the tests. The reference values for magnitude of
Pearson’s correlation coefficient are as follows: up to .30 negligible, .31 to .50 low, .51 to .70 moderate, .71 to -.90 high, and .91 to 1.0
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Special issue:
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very high
33
. Squared correlation values (r
p
2
) are presented as a quantification of shared variance. Analyses were performed by using
SPSS software (v.24, IBM Statistics, USA), with statistical significance set at p <.05.
RESULTS
Data from all tests were normally distributed. Data from one outlier (2 standard deviations above the mean) were excluded for
the following tests: TUGC, TUGDT and FTSS. Raw data are available as Supplementary material.
Comparison between the three versions of the Timed Up and Go test
Completion time
The results for completion time indicated a significant effect of TUG version, F(2, 40) = 18.46, p <.01, η
p
2
=.48. Post hoc
comparisons indicated significant differences in all comparisons, as follows: (1) TUG
DT
> TU
GC
(p =.02), (2) TUG
OL
> TUG
C
(p <.01), and
(3) TUG
OL
> TUG
DT
[p =.01] (Figure 1A).
RMS
ml
trunk acceleration
Results for RMS
ml
trunk acceleration indicated a significant effect of TUG version, F (2, 40) = 8.63, p <.01, η
p
2
=.30. Post hoc
comparisons indicated the following significant differences: higher acceleration values for the TUG
C
compared to TUG
DT
and TUG
OL
(p
values <.01), with lack of a significant difference between the latter (Figure 1B).
Figure 1.!Comparison between mean values (standard errors in bars) between (A) completion time and (B) RMS
ML
of the three TUG versions; *p <.05
Correlation between RMS
ml
and completion time
Timed Up and Go
Analysis indicated high negative correlation between completion time and trunk acceleration for the conventional (r
p
= -.71, r
p
2
=.50, p <.01, Figure 2A) and dual-task (r
p
= -.77, r
p
2
=.59, p <.01, Figure 2B) TUG versions, while for the overline TUG version a
negligible correlation was found (r
p
= -.06, r
p
2
= zero, p =.82, Figure 2C).
Five Times Sit-to-Stand (FTSS)
Results for the FTSS test showed a high positive correlation (rp =.73, rp2 =.53, p <.01) between completion time and trunk
acceleration (Figure 2D).
0
2
4
6
8
10
12
Completion time (s)
A
*
0.0
0.5
1.0
1.5
2.0
2.5
3.0
TUGC TUGDT TUGOL
ML trunk acceleration (mm/s
2
)
B
TUG
C
TUG
DT
TUG
OL
*
*
*
*
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Figure 2.!Correlation between completion time and root mean square (RMS) of mediolateral lower trunk acceleration in each test: (A) conventional TUG (TUG
C
),
(B) dual-task TUG (TUG
DT
), (C) overline TUG (TUG
OL
), and (D) Five Times Sit-to-Stand (FTSS)
Correlation between tests
The correlation analysis of completion time between tests indicated a high correlation between TUG
C
and TUG
DT
(r
p
=.71, rp2
=.50, p <.01). Results for ML trunk acceleration indicated a high correlation between TUG
C
and TUG
DT
(r
p
= .78, r
p
2
= .60, p < .01), and
moderate correlations between TUG
C
and TUG
OL
(r
p
= .54, r
p
2
= .29, p = .05), TUG
OL
and FTSS (r
p
= .67, r
p
2
= .44, p < .01), and TUG
DT
and TUG
OL
(r
p
= .52, r
p
2
= .27, p = .05) (Figure 3).
Figure 3.!Correlation of root mean square (RMS) of mediolateral trunk acceleration between the following: (A) conventional TUG (TUG
C
) and dual task TUG
(TUG
DT
), (B) conventional TUG and overline TUG (TUG
OL
), (C) overline TUG and Five Times Sit-to-Stand (FTSS), (D) overline TUG and dual task TUG.
DISCUSSION
This study aimed to evaluate the correlation of completion times observed in the FTSS and in different versions of the TUG test
with acceleration-based measurement of trunk stability and to compare conventional and a new version of the TUG test. The results
indicated that the overline TUG test led to a longer completion time than the conventional and dual-task versions of this test, while trunk
acceleration values were lower for the overline and dual-task versions than the conventional version. As a primary outcome, correlation
analysis showed a strong negative correlation between completion time and trunk acceleration for the conventional and dual-task TUG
versions, while no such a correlation was found for the overline version. A positive correlation between completion time and trunk
acceleration was found for the FTSS test only. As a secondary outcome, we found moderate to high correlations for ML trunk
r
p
= - 0.71
0
1
2
3
5 6 7 8
RMS
ml
(mm/s
2
)
TUG
C
r
p
= - 0.78
0
1
2
3
5 7 9 11
RMS
ml
(mm/s
2
)
TUG
DT
B
r
p
= - 0.06
0
1
2
3
5 7 9 11
RMS
ml
(mm/s
2
)
Time (s)
TUG
OL
C
r
p
= 0.74
0.0
0.5
1.0
1.5
2.0
5 7 9 11
RMS
ml
(mm/s
2
)
Time (s)
FTSS
D
A
1.0
1.5
2.0
2.5
1.5 2.0 2.5 3.0
TUG
DT
- RMS
ml
(mm/s
2
)
TUG
C
- RMS
ml
(mm/s
2
)
A
r
p
= 0.78
1.0
1.5
2.0
2.5
1.5 2.0 2.5 3.0
TUG
OL
- RMS
ml
(mm/s
2
)
TUG
C
- RMS
ml
(mm/s
2
)
B
r
p
= 0.54
0.0
0.5
1.0
1.5
1.0 1.5 2.0 2.5
FTSS - RMS
ml
(mm/s
2
)
TUG
OL
- RMS
ml
(mm/s
2
)
r
p
= 0.67
C
1.0
1.5
2.0
2.5
1.0 1.5 2.0 2.5
TUG
OL
- RMS
ml
(mm/s
2
)
TUG
DT
- RMS
ml
(mm/s
2
)
r
p
= 0.52
D