Assessment of Shoulder Girdle Elevation Motion using Daid Smart
Shirt: A Reliability and Validity Study
Guna Semjonova
1 a
, Janis Vetra
1
, Aleksandrs Okss
2
, Aleksejs Katashevs
2
and Vinita Cauce
1
1
Riga Stradins University, Dzirciema Street 16, Riga, Latvia
2
Riga Technical University, Kalku Street1, Riga, Latvia
Keywords: Wearable Technology, Knitted Strain Sensors, Shoulder Motion Assessment, Validity, Reliability.
Abstract: Muscle function around the shoulder girdle can be impaired by pain, which leads to abnormal movement e.g.
elevation. Movement faults should be assessed specifically, therefore individual sport rehabilitation strategies
can be implemented. Smart garments are efficient for upper body movement assessment. There is a lack of
literature stating that smart textile garments are reliable and valid for shoulder gridle elevation. The purpose
of the study was to examine reliability and validity of the DAid smart shirt during shoulder girdle elevation.
Twenty-one female volunteers aged 24.3. (SD3.3), body mass index 19.3 (SD 0.5) were recruited. The DAid
smart shirt and 2D movement video analysis software Quintic Biomechanics v26, UK were the assessment
tools utilized. Cronbach alpha coefficient and Interclass Correlation Coefficient were calculated to assess the
within-session test-retest reliability. Bland Altman analysis was applied to determine validity. Results:
reliability for the right side measures: Cronbach alpha coefficient α 0.9, ICC ≥ 0.9. Reliability for the left
side measures: Cronbach alpha coefficient α 0.9, ICC 0.91. Bland -Altman analysis presents that DAid
smart shirt measures are valid during shoulder girdle elevation. Conclusion: smart shirt measures are reliable
and valid during shoulder girdle elevation movements.
1 INTRODUCTION
Shoulder pain affects 22.3% of people, with
significant detrimental impact on health-related
quality of life and physical functioning (Hill et al,
2010). There is high prevalence of shoulder pain in
the populations of overhead athletes, with reports of
12% in amateur golf (McHardy, Pollard and Luo,
2007 ), 16% in volleyball (Clarsen et al., 2014), 22%
to 36%% in elite handball (Myklebust et al., 2011)
and 24% in high-level adolescent tennis, which
increases to 50% in middle-aged tennis players
(Abrams et al, 2012). The prevalence of shoulder pain
is even higher in swimmers, ranging between 40%
and 91% (Wanivenhaus et al., 2012).
Evidence suggests that muscle function around
the shoulder girdle can be impaired by pain and
pathology. Altered timing (latency) of
electromyographic (EMG) activity has been
identified in muscles of the scapula and the
glenohumeral joint. Motion analysis studies have
identified abnormal movements of the scapula which
a
https://orcid.org/0000-0002-6554-0716
include elevation, internal rotation of the scapula, and
anterior tilt. Alterations in the dynamic control of
scapula-thoracic joints are important factors in
shoulder pathology. Literature supports the need for a
specific assessment of movement faults, so individual
rehabilitation strategies can be implemented
(Comerford and Mottram, 2012).
There is a wide range of healthcare applications
to smart garments, including rehabilitation (Wang et
al., 2017), prevention of shoulder injury in overhead
sports (Rawashdeh et al., 2016) and enhance physical
therapy treatment, e.g., for treating shoulder
musculoskeletal disorders and pain (Wang et al,
2017). One of the main parts of smart garments is the
sensing system which can include one or several
sensing elements for posture and joint motion control
and assessment (Wang et al., 2017). The smart
garment system is efficient for upper body movement
assessment during simple tasks (Wang et al., 2017)
and a customized smart shirt can be an objective and
convenient device for shoulder motion capture and
monitoring during advanced motor tasks such as
Semjonova, G., Vetra, J., Okss, A., Katashevs, A. and Cauce, V.
Assessment of Shoulder Girdle Elevation Motion using Daid Smart Shirt: A Reliability and Validity Study.
DOI: 10.5220/0008064802290235
In Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2019), pages 229-235
ISBN: 978-989-758-383-4
Copyright
c
2019 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
229
shoulder motor control exercises and ballet training
sessions (Semjonova et al., 2018).
However, there is a lack of literature supporting
that DAid smart shirts are reliable and valid for the
assessment of shoulder girdle elevation motions.
This study aims to examine the reliability and
validity of the DAid smart shirt measures during
shoulder girdle elevation motions.
2 METHODOLOGY
2.1 Participants
Twenty-one healthy participants of age 24.2 (SD 3.3)
were recruited on a voluntary basis. Their Body Mass
Index was 19.3 (SD 0.5). Body mass index was (BMI)
calculated from self-reported weight (kg) and height
(m) according to WHO (World Health Organization)
Regional office for Europe guidelines. Participants
were excluded if they reported any current neck or
shoulder pain, or a history of major trauma to the neck
or shoulder (e.g. dislocations, fractures or surgery).
Participants gave written informed consent for
inclusion before they participated in the study. The
study was conducted in accordance with the
Declaration of Helsinki, and the study protocol was
approved by the Ethics Committee of Riga Stradins
University (183/26.01.2017).
2.2 Instrumentation
DAid Smart shirt was used to capture and monitor
shoulder girdle motion during a research task for the
participants. This smart garment was developed in
collaboration between Riga Technical University and
Riga Stradins University for posture assessment
(Semjonova et al, 2018).
The DAid Smart shirt presents a tight shirt with
four embedded highly sensitive knitted strain sensors
(Oks et al, 2014). Sensor reactions are transferred via
sewn electro conductive pathways to an electronic
device acquiring the data and then via Bluetooth to a
computer or tablet. The specific placement of the
sensor provides independence of the sensors
reactions to patient’s shoulder elevation-depression
movements. ADC 1 left side shoulder elevation;
ADC 2 right side shoulder elevation; ADC 3 right
side shoulder protraction; ADC 4 left side shoulder
protraction (Fig.1).
The two camera 2D optical motion capture system
Quintix Biomechanics v26 (UK) was used to record
the positional data of the reflective markers
(diameter: 10 mm) at 100 samples/s. Four reflective
Figure 1: Participant with a smart shirt with sensors and
reflective markers for the motion capture system during
intervention.
markers were attached to the DAid smart shirt over
scapular anatomical landmarks: on the right and left
side angulus acromialis (R_AA, L_AA); the right and
left side trigonum spinae scapulae (R_TS, L_TS) in a
neutral standing posture (Fig.1). According to the
recommendation of the International Society of
Biomechanics (USA) on definitions of joint
coordinate systems of various joints for the reporting
of human joint motionPart II: shoulder, elbow,
wrist and hand (Wu et al., 2005).
2.3 Intervention
Participants stood with their feet shoulder width apart
and arms by their side and performed a standardized
familiarization and warm-up procedure of moving
their scapula into the end range clavicle movements.
Participants were instructed to: ‘move the right
shoulder girdle as far up as they can’ (elevation), ‘as
far down’ (depression). This process was repeated
three times (10s rest between repetitions) and one-
minute rest between the conditions was given to avoid
fatigue (Bet - Or et al., 2017). The metronome was
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230
used for counting seconds. The Metronome Beats
Mobile App in Sony Xperia™ smartphone was set at
60 bpm. Each recording length was 13 seconds.
2.4 Data Statistical Analysis Methods
Descriptive statistical analysis was carried out to
describe the study population. The reliability and
validity of values of the smart shirt in millivolts (mV)
and the angle values of the optical motion capture
system in degrees were analysed using IBM SPSS
Statistics 22.0 software (IBM Corporation, New
York, USA) and Microsoft Excel 2010.
To assess the within-session test-retest reliability
for repeated measure units (mV) during the task,
Cronbach α coefficient (a Cronbach’s α 0.70 was
considered reliable) and Interclass Correlation
Coefficient (ICC) was calculated. Inter-rater
reliability was considered poor for ICC values less
than 0.40, fair for values between 0.40 and 0.59, good
for values between 0.60 and 0.74, and excellent for
values between 0.75 and 1.0 (Cicchetti et al., 2006).
To assess the validity within two quantitative
methods, Bland Altman analysis was applied. The
Bland-Altman analysis plot describes the agreement
between the quantitative measurements by
constructing limits of agreement. These statistical
limits are calculated by using the mean value and the
standard deviation and the 95% confidence interval
for the limits of the differences between two
measurements. To check the assumptions of
normality of differences and other characteristics,
Bland Altman system uses a graphical approach
(Giavarina, 2015).
3 RESULTS
All data from the DAid smart shirt and optical motion
capture system Quintix Biomechanics v26 were
imported to the Microsoft Excel 2010 programme.
The ACD 1 sensor, ACD 2 sensor and time values
where extracted from other unnecessary data. The
angular degree and time values of the left and right-
side shoulder girdle elevation motions were extracted
from the optical motion capture system. The system
data were gathered in one common sheet in Microsoft
Excel 2010 programme. Visual graphs were made for
all the three repeated measures on the left-side
(Appendix.Fig.8, Fig.9, Fig.10.) and right-side
(Fig.2., Fig.3., Fig.4.), for all 21 participants.
Figure 2: First measure for the right-side shoulder elevation
motion.
Figure 3: Second measure for the right-side shoulder
elevation motion.
Figure 4: Third measure for the right-side shoulder
elevation motion.
Only data from the ACD 1 sensor left shoulder
elevation and the ACD2 sensor right shoulder
elevation were analysed. Disadvantages were
established in capturing protraction movement with a
two-camera 2D optical motion capture system
Quintix Biomechanics v26 (UK).
3.1 Reliability
To calculate reliability and validity of the DAid smart
shirt as compared with the gold standard of the
Assessment of Shoulder Girdle Elevation Motion using Daid Smart Shirt: A Reliability and Validity Study
231
motion capture system: an optical motion capture
system in laboratory environment, data from
Microsoft Excel 2010 were imported to IBM SPSS
Statistics 22.0 software,
After three repeated measures, the ACD 1 left side
results show excellent ICC and Cronbach’s α
coefficient values. ICC values: 0.91 (95%CI 0.9 -
0.92) 0.99 (95%CI 0.99 0.99) (p ˂ 0,0001).
Cronbach’s α coefficient values: 0.91 0.99. The data
from ACD 2 right shoulder elevation shows
excellent ICC and Cronbach’s α coefficient values.
ICC values: 0.91 (95%CI 0.9 - 0.91) 0.99 (95%CI
0.99 0.99) (p ˂ 0,0001). Cronbach’s α coefficient
values: 0.91 0.99 during intervention.
3.2 Validity
Bland Altman analysis was applied to assess the
validity of the DAid smart shirt measurements and
optical motion capture system Quintix Biomechanics
v26 as the “gold standard”.
The left and right-side 8 s elevation motion
duration was divided into 0.5s intervals. Plots of
Bland Altman analysis were created for the right and
left-side shoulder elevation motion interval of each
0.5s. There were 16 Bland-Altman plots for the right-
side shoulder and 16 Bland-Altman plots for the left
side shoulder.
First, to compare the values, the amplitude values
in millivolts (mV) and the optical motion capture
system shoulder elevation angle values in degrees in
the DAid smart shirt shoulder elevation motion were
normalized.
Second, for the Y axis, the difference between a
normalized (N) DAid smart shirt and a normalized
(N) Quintix v26 optical motion analysis system
values were calculated. For the X axis, the average of
these normalized values was calculated. Afterwards,
horizontal lines were drawn: the mean difference and
the limits of agreement as 95% confidence interval
(CI), which are defined as the mean difference plus
and minus 1.96 times the standard deviation of the
differences (Fig.5.).
Bland Altman recommended that 95% of the data
points should lie within limit of agreement (95%
confidence interval). There can be no more than 2
data points or outliers out of limit of agreement when
comparing the normalized values of the DAid smart
shirt and the normalized values of the Quintix optical
motion capture system during 0.5s shoulder elevation
motion interval.
Regarding the right-side, 100% all data points
were in limit of agreement within 16 Blant Altman
plots for 0.5s motion interval. Limit of agreement
Figure 5: DAid smart shirt method and Quintix method
comparison Bland Altman plot.
minimal values for the right-side were within a 0.5s
interval of a 7s elevation motion: -0.06: 0.04 (95%
CI) (Fig.6). The maximum values of the limit of
agreement for the right-side were within a 0.5s
interval of a 1.5s elevation motion: -0.34: 0.35 (95%
CI).
Figure 6: DAid smart shirt and Quintix comparison for
right-side shoulder elevation in 7s 0.5s interval.
Left-side 15/16 Bland Altman plots shows, that
data points were in limit of agreement. There were 4
outliers from limits of agreement in 1.5s during left
shoulder elevation motion in the Bland Altman plot.
Limit of agreement minimum values for the left-side
were within a 0.5s interval of a 7.5s elevation motion:
-0.05: 0.03 (95% CI) (Fig.7). Limit of agreement
maximal values for left-side were within a 0.5s
interval of a 4.5s elevation motion: -0.25: 0.31(95%
CI).
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232
Figure 7: DAid smart shirt and Quintix comparison for left-
side shoulder elevation in 7.5s 0.5s interval.
4 DISCUSSION
This study was performed to examine the reliability
and validity of the DAid smart shirt measures during
shoulder girdle elevation motion.
As significant amount of literature on shoulder
motion analysis and optical motion capture systems
recording the positional data of the reflective markers
identified abnormal movements of the scapula which
include elevation (Comerford and Mottram, 2012), a
specific assessment of movement faults should be
implemented to build individual rehabilitation
strategies.
The present study revealed that the DAid smart
shirt is reliable and valid to assess shoulder girdle
elevation motion on both left and right sides
compared with the gold standard optical motion
capture system Quintix Biomechanics v26. All DAid
smart shirt measures were reliable and valid,
however, during the 1.5s left side shoulder motion
assessment there were some outliers in the Bland
Altman plot. It was also claimed in Cai et al study
(Cai et al., 2019), where they tested the concurrent
validity and the test-retest reliability of upper limb
functional assessment using low-cost marker less
motion capture system (Microsoft Kinect V2 Sensor).
The system had good accuracy in measuring shoulder
angles. However, there were also some deviations
both between the Kinect V2 system and the Vicon
system (gold standard) and between test sessions (Cai
et al., 2019).
Results show that the DAid smart shirt can
reliably measure right and left side shoulder elevation
motions and measures agree well with the optical
motion capture system. In clinical implications it
means that DAid smart shirt can be an objective and
convenient device for the assessment of abnormal
shoulder motions such as elevation.
For both: patient and physiotherapist it can be
used as an effective assisting device in addition to
conventional physiotherapy for shoulder girdle
motion capture and monitoring during shoulder
rehabilitation tasks.
The DAid smart shirt motion assessment method
is objective, which helps to quantify kinematic
parameters and turn data into a knowledge-based
data. Also, for a rehabilitation specialist e.g.
physiotherapist this is an effective assisting device,
because the therapist must not control patient’s
shoulder girdle stability during arm movement all the
therapy time, as a result therapy process is optimized,
but still effective.
Future studies are needed to evaluate these
wearable devices over an extended period, and during
rehabilitation tasks and within therapy sessions in
rehabilitation settings with patients suffering from
shoulder pain.
Several limitations apply to this study. First, the
DAid smart shirt was a one-sized compression shirt
with sewn up textile strain sensors. Second, there
were disadvantages in capturing protraction
movements with the two-camera 2D optical motion
capture system Quintix Biomechanics v26 (UK).
5 CONCLUSIONS
The present study shows that the DAid Smart shirt is
reliable and valid for the assessment of the right and
left side shoulder girdle elevation motions. The DAid
smart shirt has great potential as a low-cost, easily
implemented device for assessing abnormal shoulder
motions such as shoulder girdle elevation during
upper limb rehabilitation tasks. The system is suitable
for assessing change in upper limb motions over time,
such as disease progression or improvement due to
intervention.
ACKNOWLEDGEMENTS
This research is co-financed by the ESF within the
project «Synthesis of textile surface coating modified
in nano-level and energetically independent
measurement system integration in smart clothing
with functions of medical monitoring», Project
implementation agreement No. 1.1.1.1./16/A/020."
Assessment of Shoulder Girdle Elevation Motion using Daid Smart Shirt: A Reliability and Validity Study
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APPENDIX
Figure 8: First measure for the left-side shoulder elevation
motion.
Figure 9: Second measure for the left-side shoulder
elevation motion.
K-BioS 2019 - Special Session on Kinesiology in Sport and Medicine: from Biomechanics to Sociodynamics
234
Figure 10: Third measure for the left-side shoulder
elevation motion.
Assessment of Shoulder Girdle Elevation Motion using Daid Smart Shirt: A Reliability and Validity Study
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