Assessment of Shoulder Girdle Elevation Motion using Daid Smart

Shirt: A Reliability and Validity Study

Guna Semjonova

1 a

, Janis Vetra

, Aleksandrs Okss

, Aleksejs Katashevs

and Vinita Cauce

Riga Stradins University, Dzirciema Street 16, Riga, Latvia

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

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

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 motion—Part 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."

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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.

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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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