E Ainsworth

J M Hausdorff

L Chiari

P Van Campen

R C Van Lummel

U Lindemann

W Zijlstra

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Gait & Posture xxx (2012) xxx–xxx
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GAIPOS-3735; No. of Pages 4Short communication
Automated approach for quantifying the repeated sit-to-stand using one body
fixed sensor in young and older adults
R.C. Van Lummel a,*, E. Ainsworth a, U. Lindemann b, W. Zijlstra c, L. Chiari d, P. Van Campen e,
J.M. Hausdorff f
a McRoberts, Raamweg 43, 2596 HN The Hague, The Netherlands
b Robert-Bosch-Hospital, Department of Clinical Gerontology, Auerbachstr. 110, 70376 Stuttgart, Germany
c Center for Human Movement Science, University Medical Center Groningen, University of Groningen, 9700 AD Groningen, The Netherlands
d Department of Electronics, Computer Science and Systems, University of Bologna, 40136 Bologna, Italy
e Van Campen Physiotherapy, The Hague, The Netherlands
f Tel Aviv Sourasky Medical Center, Laboratory for Gait and Neurodynamics, Movement Disorders Unit, Department of Neurology and Department of Physical Therapy, Sackler Faculty
of Medicine, Tel-Aviv University, 64239 Tel-Aviv, Israel
A R T I C L E I N F O
Article history:
Received 5 August 2011
Received in revised form 11 May 2012
Accepted 9 October 2012
Keywords:
Sit-to-stand
Body fixed sensors
Accelerometers
Gyroscopes
Automated analyses
Older adults
A B S T R A C T
Much is known about the sit-to-stand (STS) and its biomechanics. Currently, however, there is little
opportunity for instrumented quantification of the STS as part of screening or diagnosis in clinical
practice. The objectives of the present study were to describe the feasibility of using an automated
approach for quantifying the STS using one sensor location and to start testing the discriminative validity
of this approach by comparing older and younger adults. 15 older subjects recruited from a residential
care home and 16 young adults performed 5 repeated sit-to-stand and stand-to-sit movements. They
were instrumented with a small and lightweight measurement system (DynaPort1) containing 1 triaxial
seismic accelerometer and 3 uniaxial gyroscopes fixed in a belt around the waist. Durations of the (sub-
)phases of the STS were analyzed and maximum angular velocities were determined. All successful STS
cycles were automatically detected without any errors. The STS duration in the older adults was
significantly longer and more variable in all phases (i.e., sit-to-stand, standing, stand-to-sit and sitting)
compared to the young adults. Older adults also exhibited lower trunk flexion angular velocity. The
results of this first fully automated analysis of instrumented repeated STS movements demonstrate that
several STS parameters can be identified that provide a basis for a more precise, quantitative study of STS
performance in clinical practice.
 2012 Elsevier B.V. All rights reserved.
Contents lists available at SciVerse ScienceDirect
Gait & Posture
jo u rn al h om ep age: ww w.els evier .c o m/lo c ate /g ai tp os t1. Introduction
Previous work using camera-based systems and force plates in
laboratory settings has quantified sit-to-stand (STS) movements
to better understand their biomechanical dynamics [1,2]. Body
fixed sensors (BFS) were introduced to movement analysis
research in the early 1990s [3] and offer an alternative approach
to quantifying the STS. Studies using BFS demonstrated the ability
to identify the beginning and end of STS transitions with one
gyroscope fixed to the chest [4]. Accelerometers fixed to the
sternum and to the upper leg were used to detect the start and end
of a STS transition in healthy subjects and stroke subjects [5].
Using accelerometers and gyroscopes, the kinematics of rising
from a chair were calculated [6]. Power during STS movements has
been recently analyzed by adding magnetic-field sensors [7].* Corresponding author. Tel.: +31 70 310 6462; fax: +31 70 316 4103.
E-mail address: rcvanlummel@mcroberts.nl (R.C. Van Lummel).
Please cite this article in press as: Van Lummel RC, et al. Automated a
fixed sensor in young and older adults. Gait Posture (2012), http://d
0966-6362/$ – see front matter  2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.gaitpost.2012.10.008Nonetheless, to date, automated algorithms for quantifying
repeated sit-to-stand and stand-to-sit movements using BFS
have not been described. This method is expected to be usable for
collecting quantitative STS data on a routine basis in clinical
practice. Since this is currently not possible, the objective of the
present study was to investigate the feasibility of using an
automated approach for quantifying the STS using one sensor
location and to start testing the discriminative validity of this
approach by comparing older and younger adults.
2. Methods
2.1. Subjects
In this experimental cross-sectional study, 15 older adults (OA), living in a
residential care home (11 female, median age 88 (73–99) years; median height
162 (156–192) cm; median weight 66 (44–91) kg) and 16 healthy young adults
(YA) were recruited (9 female, median age 20 (18–23) years; median height 167
(162–184) cm; median weight 62 (53–78) kg). Height and weight were not
significantly different in the two groups. All participants provided informed
written consent. The protocol was approved by the Ethics committee of the Free
University Amsterdam.pproach for quantifying the repeated sit-to-stand using one body
x.doi.org/10.1016/j.gaitpost.2012.10.008
Fig. 1. The wavelet transform of the sine of the trunk angle, dw_sin(f), is shown
during the main sub-phases of a complete STS cycle, preceded and followed by a
sitting epoch.
Fig. 2. Typical example of five repeated STS cycles of an older adult (top panel) and a you
stretched, indicated by a dotted line, for better comparibility to the young adult panel. In
sitting down is indicated by #. Variability of the signals of the OA is highand of the YA
R.C. Van Lummel et al. / Gait & Posture xxx (2012) xxx–xxx2
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GAIPOS-3735; No. of Pages 4
Please cite this article in press as: Van Lummel RC, et al. Automated a
fixed sensor in young and older adults. Gait Posture (2012), http://d2.2. Instrumentation and data acquisition
A BFS system (DynaPort1 Hybrid, McRoberts; 87 mm  45 mm  14 mm, 74 g)
was inserted in an elastic belt on the lower back positioned at the lumbar vertebra.
These included 3 pre-calibrated accelerometers (STM-LIS3LV02DQ), 3 gyroscopes
(EPSON-XV-3500CB), sampling rate 100 Hz. The accelerometer signals have been
shown to be highly reproducible [8]. Raw data were stored on a Micro-SD card
(SanDisk).
2.3. Procedure
Subjects performed 5 STS cycles at a self-selected speed (start and end in a sitting
position), while free to swing their arms. A standard chair without arm rests was
used. Subjects were video taped from the side to enable post hoc visual inspection
by a single observer of successful and failed attempts. A failed STS attempt was
defined as the subject not being able to end in a standing position.
2.4. Signal analysis
Data was corrected for tilt [9]. The acceleration and the angular velocity in the
sagittal plane determined the trunk angle (f) [10]. Subsequently, the sine of the
trunk angle (sin(f)) was calculated. Drift and noise were removed from the sin(f)
using the discrete wavelet transform dw_sin(f) [4]. ‘‘True vertical acceleration’’ was
estimated by removing the influence of f from the vertical acceleration signal.
Finally, vertical velocity was derived by integrating this signal.
The vertical velocity was used to differentiate between successful STS move-
ments and failed STS attempts. The dips in dw_sin(f) were used to detect a change
in trunk rotation direction (Fig. 1). The start of the sit-to-stand was defined as theng adult (bottom panel). In the middle panel the first 23 s of the older adult panel is
 the panels dw_sin(f) andvertical velocity are shown. Standing up is indicated by ",
 is relatively low. Duration of standing and sitting of the OA is relatively long.
pproach for quantifying the repeated sit-to-stand using one body
x.doi.org/10.1016/j.gaitpost.2012.10.008
Table 1
Durations (s), maximum angular velocity (vmax, in8/s), and coefficient of variation of durations (percentage) of the 5 repeated sit-to-stand cycles of the young and older adults.
Young adults Older adults p-Value*
Median Min Max Median Min Max
Duration (s)
Sit-to-stand Duration 1.45 1.14 2.58 1.98 1.65 3.49 <0.001
Flexion duration 0.73 0.63 0.88 1.06 0.74 1.64 <0.001
Extension duration 0.72 0.49 1.74 1.1 0.82 1.94 <0.001
Standing Duration 0.33 0 0.74 1.35 0.57 6.57 <0.001
Stand-to-sit Duration 1.47 1.18 2.28 2.59 1.34 3.21 <0.001
Flexion duration 0.69 0.46 0.91 1.31 0.65 1.87 <0.001
Extension duration 0.79 0.71 1.37 1.06 0.69 1.68 0.024
Sitting Duration 0.33 0.06 0.7 3.1 0.36 9.71 <0.001
Angular velocities (8/s)
Sit-to-stand vmaxflexion 124.62 90.04 192.7 91.62 57.31 125.46 <0.001
vmaxextension 57.22 20.7 98.9 54.67 25.57 93.33 0.323
Stand-to-sit vmaxflexion 79.68 50.32 117.63 40.93 22.99 72.71 <0.001
vmaxextension 102.15 60.42 138.22 107.31 65.65 170.29 0.527
Coefficient of variation (%)
Sit-to-stand Duration 7 2 15 26 7 42 <0.001
Flexion duration 8 5 16 19 9 41 <0.001
Extension duration 11 3 33 40 7 85 0.003
Standing Duration 40 5 96 55 26 121 0.08
Stand-to-sit Duration 8 3 39 19 7 51 0.001
Flexion duration 12 2 36 22 9 44 0.005
Extension duration 10 3 61 18 11 79 <0.001
Sitting Duration 36 8 69 57 38 140 0.002
* P-values compared the young and older adults are calculated using the Mann–Whitney U-test (p < 0.05).
R.C. Van Lummel et al. / Gait & Posture xxx (2012) xxx–xxx 3
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GAIPOS-3735; No. of Pages 4end of the plateau before the first dip in dw_sin(f). Similarly, the end of the sit-to-
stand was defined as the start of the plateau after the first dip in dw_sin(f). The start
of the stand-to-sit was defined as the end of the plateau before the second dip in
dw_sin(f) and the end of the of the stand-to-sit was defined as the start of the
plateau after the second dip in dw_sin(f). Plateaus were identified where the slope
of dw_sin(f) was smaller than 0.1. After automated identification of all phases (sit-
to-stand and stand-to-sit) and sub-phases (flexion and extension), durations,
coefficients of variation of all durations (CV) and maximum angular velocity were
calculated. Only subjects who completed all 5 repetitions were included in the
analysis of the CV.
To evaluate the feasibility of the automated method, we documented the % of STS
movements that correctly identified using the BFS and compared that to those
identified by the observer.
2.5. Statistical analysis
Due to the small sample size and non-normal distribution of some measures,
parameters are described using median, minimum and maximum values.
Differences in outcomes between OA and YA were analyzed using the Mann–
Whitney U-test (p < 0.05) (SPSS version 17.0).
3. Results
All 16 young controls were able to complete the 5 STS cycles.
Twelve of the OA completed all 5 STS cycles, three completed at
least 1 cycle. The data of all subjects were included in the analysis
of duration and angular velocity.
From the 12 OA who completed the 5 repetitions, 3 had failed
efforts to rise from the chair. All (100%) of the failed attempts were
detected as such by the software and all successful transitions
were correctly identified. Fig. 2 illustrates an example of the
dw_sin(f) of the trunk angle and the vertical velocity of five STS
cycles of a typical OA and YA. The variability of the signal and the
durations of the phases of the older adult are high. Nonetheless, all
sit-to-stand and stand-to-sit transitions were correctly detected by
the software without manual interference.
All durations were significantly longer for the OA (Table 1). The
median of the summed time of standing and sitting was 4.45 s and
0.66 s for OA and YA, respectively, representing 49% and 18% of the
total STS cycle time. The maximum angular velocity was lower for
the OA during the flexion phases of sit-to-stand and stand-to-sit
than for the YA (p < 0.001), but not during the extension phases. AllPlease cite this article in press as: Van Lummel RC, et al. Automated a
fixed sensor in young and older adults. Gait Posture (2012), http://dbut one (standing phase) of the CV scores were significantly higher
for OA than for YA (Table 1).
4. Discussion and conclusions
The present findings demonstrate that automated analyses of
repeated STS data captured using a single BFS is feasible. The
software was able to correctly detect durations and maximum
angular velocity of all successfully completed sit-to-stand and
stand-to-sit cycles.
The automated detection also identified many features of the
STS that were different in this small sample of older and young
adults. Future work is needed to identify parameters that are most
sensitive to aging and intervention. Duration parameters were
chosen to differentiate between the duration of different phases.
The angular velocity parameters were chosen because in other
studies they relate to moments, which might be critical for
successful STS transition. CV parameters were chosen because they
might show loss of automation. The initial findings suggest that
these three different sets of parameters may have clinical utility.
Further validation in a larger sample size and in patients who
may have more disturbed STS patterns are needed to confirm the
present findings and identify the most relevant parameters.
Nonetheless, the results of this first fully automated analysis of
instrumented repeated STS movements demonstrate that several
STS parameters can be identified that provide a basis for a more
precise, quantitative study of STS performance, in clinical practice.
Acknowledgements
The project was partly funded by the European Commission
(FP6 project SENSACTION-AAL, IST-045622). We thank Residential
Care Home Duinhage and the young and older adults who
participated.
Conflict of interest
R.C.V.L. is the owner and E.A. is an employee of McRoberts B.V.
This company is the manufacturer of the DynaPort.pproach for quantifying the repeated sit-to-stand using one body
x.doi.org/10.1016/j.gaitpost.2012.10.008
R.C. Van Lummel et al. / Gait & Posture xxx (2012) xxx–xxx4
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Automated approach for quantifying the repeated sit-to-stand using one body fixed sensor in young and older adults

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Automated approach for quantifying the repeated sit-to-stand using one body fixed sensor in young and older adults

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