Inter-session Test-retest Reliability of the Quantified Y Balance Test

William Johnston

1,2

, Martin O’Reilly

1,2

, Garrett F. Coughlan

and Brian Caulfield

1,2

Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland

School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland

Connacht Rugby, The Sportsgrounds, College Road, Galway, Ireland

Keywords: Dynamic Balance, Digital Biomarker, Inertial Sensor, Y Balance Test, Reliability, Inter-session.

Abstract: The Y Balance test is the most common dynamic balance assessment used in clinical practice and research.

However, the traditional measure of performance, the reach distance, fails to provide detailed information

pertaining to the control of balance during the reach task. Recent research has demonstrated that a single

wearable inertial sensor can capture detailed information pertaining to balance performance during the Y

balance test, not captured by the traditional reach distances. To date, no research has been conducted

investigating the inter-session test-retest reliability of the inertial sensor instrumented YBT. Thirty -two young

healthy adults, aged between 18-40 were recruited as part of this study. Participants completed the quantified

YBT protocol during two testing sessions, separated by 7-10 days. The findings from this study demonstrated

that 26/36 (anterior), 31/36 (posteromedial) and 33/36 (posterolateral) quantified variables demonstrated

good-excellent intra-session test-retest reliability. These findings suggest that the inertial sensor quantified

YBT can provide a reliable measure of dynamic balance performance. Further research is required to

investigate the capability of the quantified YBT to identify individuals at risk of injury/ disease and track

recovery/ response to intervention.

1 INTRODUCTION

The Y Balance Test (YBT) is one of the most

commonly utilised clinical dynamic balance

assessment tools (Gribble et al., 2012). It provides a

valid and reliable measure of balance performance,

requiring the individual to maintain their balance

while completing a maximal reach in three prescribed

directions; anterior (ANT), posteromedial (PM) and

posterolateral (PL). Traditionally, the test is scored by

manually measuring the distance the individual

reaches outside of their base of support (Plisky et al.,

2009). The reach distance is then typically normalised

to the individuals leg length to allow for appropriate

comparison between individuals, and between

dominant and non-dominant legs (Gribble et al.,

2012). A large body of evidence has evolved

demonstrating the utility of the YBT as an outcome

measure following injury, identifying differences in

performance between control and pathological

groups with conditions such as lateral ankle sprains

(Doherty et al., 2015), chronic ankle instability

(Holden et al., 2016) and anterior cruciate ligament

injury’s (Herrington et al., 2009). Furthermore,

previous research has demonstrated the role of the

YBT in ankle injury risk-factor screening (Plisky et

al., 2006, Smith et al., 2015).

While the traditional analogue measure obtained

from the YBT provides a measure of the distance

reached outside of the base of support, it fails to

provide quantifiable information relating to the

control of balance, or the strategy implemented

during the task. As such, individuals must rely on

subjective observations of the individual’s control or

use expensive laboratory-based force platform and

camera-based motion-capture systems that require a

high level of expertise.

Advances in mobile technology have allowed for

the development of wearable inertial sensor based

digital biomarkers of motor function. These

assessments range from static balance assessments

such as the balance error scoring system, to dynamic

gait assessments such as the timed up and go (Greene

et al., 2017, Weiss et al., 2014, Heldman et al., 2017,

Alberts et al., 2015). Recent research has established

that an inertial sensor worn on the lumbar spine can

provide a sensitive measure of balance performance,

capturing subtle alterations, not captured by the

traditional reach distances alone (Johnston et al.,

2016, Johnston et al., 2017b). These findings suggest

Johnston, W., O’Reilly, M., Coughlan, G. and Caulﬁeld, B.

Inter-session Test-retest Reliability of the Quantiﬁed Y Balance Test.

DOI: 10.5220/0006958300630070

In Proceedings of the 6th International Congress on Sport Sciences Research and Technology Suppor t (icSPORTS 2018), pages 63-70

ISBN: 978-989-758-325-4

that the quantified YBT may have value in providing

a more sensitive measure of injury/disease-risk and

recovery, across a range of clinical populations

(Johnston et al., 2017b).

Prior to the deployment of quantified YBT in a

clinical setting, it is necessary to investigate the

reliability of the inertial sensor derived variables.

Doing so will allow for the identification of the most

valuable and clinically applicable variables for

quantifying balance performance. Previous research

has demonstrated the excellent intra-session test-

retest reliability of the 95% ellipsoid volume variable

derived from the inertial sensor during the YBT (ICC

= 0.76-0.92). However, no research has investigated

the inter-session test-retest reliability of the

quantified YBT or established the relationship

between the quantified variables and the traditional

reach distances.

As such, the aim of this research is to determine

the intersession test-retest reliability of inertial sensor

derived measures of YBT performance. It is

hypothesised that the inertial sensor derived variables

will demonstrate good-excellent levels of inter-

session test-retest reliability.

2 METHODS

2.1 Participants

Thirty-two young healthy adults aged between 18-40

were recruited from the wider university population

(sex: 14 females, 18 males; age: 28 ± 5 years; height:

164 ± 37 cm; weight: 73 ± 26 kg; right leg length: 93

± 7 cm). Participants were considered eligible for this

study if they were a young healthy adult, aged

between 18-40 years. Participants were excluded if

they reported any vestibular, visual, neurological or

musculoskeletal impairment that may influence their

balance. Ethical approval was sought and obtained

from the University human research ethics

committee, and all participants provided informed

consent prior to participating in the study. All

participants read the information leaflet and were

informed of their right to withdraw from the study at

any point.

2.2 Measures

2.2.1 YBT

The YBT is an instrumented alternative to the star

excursion balance test (SEBT), designed to provide a

measure of dynamic balance performance. The YBT

leverages three of the eight original SEBT reach

directions (ANT, PM, PL) and provides a valid and

reliable measure of dynamic balance capability

(Plisky et al., 2009). Previous research has

demonstrated excellent intra-session test-retest

reliability (ICC = 0.85 - 0.88) and inter-tester

reliability (ICC = 0.99 - 1.00) of the YBT testing

apparatus (Plisky et al., 2009). The YBT requires an

individual to stand on one leg, place their hands on

their hips, and slide a block as far as possible in the

three discrete directions using their toe, while

maintaining their balance equilibrium (figure 1). The

maximal distance of the reach is then recorded.

Individuals are required to repeat the reach direction

if they (1) use the block for support, (2) remove one

or both hands from their hips, (3) kick the block

forward for extra distance, (4) make contact with the

ground or (5) raise the heel of the stance leg from the

platform.

2.2.2 Inertial Sensor

A single Shimmer3 (Shimmer, Dublin, Ireland)

inertial sensor was mounted at the level of the fourth

lumbar vertebra. The Shimmer3 consists of a tri-axial

accelerometer, gyroscope and magnetometer. It was

connected via Bluetooth to an Android tablet (Galaxy

Tab 2, Samsung), operating a custom developed

mobile application. The inertial sensor was calibrated

and configured to stream tri-axial accelerometer (± 2

g), tri-axial gyroscope (±500 ◦/s) and tri-axial

magnetometer (±1.9 gauss) data at sampling

frequency of 51.2 Hz. These data acquisition

parameters were chosen based on previous research

carried out related to the use of inertial sensors in the

quantification of the YBT (Johnston et al., 2017b,

Johnston et al., 2017a).

2.3 Testing Protocol

Participants were recruited to attend two 20-minute

testing sessions conducted in a University

biomechanics laboratory, separated by 7-10 days.

Throughout the remainder of the paper the two testing

points are referred to as week 1 (testing day 1) and

week 2 (testing day 2). On arrival to the laboratory for

the week 1 assessment, the testing protocol was

explained, and participant demographic information

was obtained. Leg dominance was determined by

asking participants which leg they would use to kick

a ball (Wilkins et al., 2004). Leg length was found by

measuring the distance from the anterior iliac spine to

the inferior border of the medial malleolus. All leg

length measurements were completed by a single

icSPORTS 2018 - 6th International Congress on Sport Sciences Research and Technology Support

Chartered Physiotherapist to ensure measurement

consistency.

During both testing sessions (week 1 and week 2),

participants completed 4 practice trials in each

direction, bilaterally, as per the YBT guidelines

developed by Gribble and colleagues (2012).

Following the practice trials, a single inertial sensor

was mounted at the level of the fourth lumbar

vertebrae, in line with the top of the iliac crest. This

location was chosen as the region between L3-L5 is

reported to closely match estimates of the body’s

centre of mass acceleration (Moe-Nilssen, 1998,

Zijlstra and Hof, 2003), and allow for easy and

repeatable placement of the sensor. The inertial

sensor was mounted using a custom-made elastic and

Velcro belt. Figure 1 illustrates the sensor mounting

location, orientation and the three reach directions of

the YBT.

Figure 1: illustrates the sensor mounting location, axis

orientation and YBT reach directions during right leg

stance.

Participants completed three recorded YBTs in

each direction (randomised order) on their right leg.

If a participant failed to complete a reach attempt

according to the criteria outlined in section 2.2.1, that

reach was discarded and repeated. Traditional YBT

reach distances were obtained by recording the

maximal reach distance, while the inertial sensor data

was capture for the period that the participant was in

unilateral stance. YBT reach distances and inertial

sensor data was recorded locally, and processed

offline using MATLAB (2017b, Mathworks,

Natwick, USA).

2.4 Data Processing

The analogue reach distances obtained during the

assessment were normalised against the participants

leg length using the following formula:











100

(1)

Nine signals were obtained from the inertial sensor;

accelerometer (accel) x, y, z, gyroscope (gyro) x, y, z

and magnetometer x, y, z. Ten additional signals were

then calculated. The 3-D orientation of the inertial

sensor was computed using the gradient descent

algorithm developed by Madgwick et al., (2011). The

resulting w, x, y and z quaternion values were then

converted to pitch, roll and yaw. The magnitude

(mag) of the accel and gyro signals were computed

using the vector magnitude of the accel x, y, z and

gyro x, y, z, respectively. Finally, the angular

acceleration was obtained by computing the first

derivative of the gyroscope y signal.

For each relevant collected and derived sensor

signal, the root-mean-square (RMS), variance and

range variables were computed with the standard

Matlab ‘rms’, ‘var’ and ‘range’ functions

respectively. The sample-entropy (sEN) was

computed for each signal of length

N=(x_1,x_2,x_3,…,x_N ) according to the following

formula:

  log



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(2)

A was the number of template vector pairs having a

Chebyshev distance 

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length m+1 and B was the number of template vectors

pairs having 

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the embedding dimension, m, was equal to 2 and the

tolerance, r, was equal to 0.1. The template vectors

were defined such that

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. The area under the

curve of the fast-fourier transform (FFT) was found

for each relevant signal by first using the Matlab ‘fft’

function (Matlab, 2018b) to derive a power-frequency

plot and then using the ‘cumsum’ function to find the

area under the curve (AUC) (Matlab, 2018a). 95%

ellipsoid volume of sway (95EV) was computed

using the following formula:

95  4πabc/3 (3)

Whereby, ‘a’ and ‘b’ are the linear acceleration in the

medio-lateral axis (accelerometer x) and anterio-

posterior axis (accelerometer z) and c was transverse

plane rotational acceleration (first derivative of

gyroscope y) (Johnston et al., 2017b).

2.5 Statistical Analysis

Descriptive statistics (means and standard deviations)

were used to describe the population and traditional

and inertial sensor YBT scores. The average of the

three trials for each reach direction was calculated for

the reach distance and inertial sensor derived

Inter-session Test-retest Reliability of the Quantiﬁed Y Balance Test

variables. This was completed to ensure measurement

reliability (Gribble et al., 2012). A 2-way random

effects, absolute agreement model of intraclass

correlation coefficient (ICC 2, k) was employed to

investigate the inter-session test-retest reliability of

the traditional and inertial sensor instrumented

measures of YBT performance. The ICCs were

calculated leveraging the mean of the three trials from

the week 1 and week 2 assessment points. The

guidelines for interpretation outlined by Cicchetti and

Sparrow (1981) were used for interpretation: <0.40

(poor reliability), 0.40–0.59 (fair reliability), 0.60–

0.74 (good reliability), and 0.75–1.00 (excellent

reliability).

3 RESULTS

Tables 1 presents the descriptive statistics for the

YBT variables, while table 2 summarises the inter-

session test-retest reliability scores for the ANT, PM

and PL reach directions. When considering the

traditional reach distances scores, it was observed that

the ANT reach direction possessed excellent

reliability, while the PM and PL directions possessed

good reliability. Twelve of the 36 ANT direction

inertial sensor derived variables demonstrated

excellent reliability, 14 demonstrated good reliability,

7 possessed fair reliability, while a further 3 had poor

reliability. Secondly, 14 of the 36 PM reach direction

inertial sensor variables demonstrated excellent

reliability, 17 had good reliability, 3 had fair

reliability, while 2 had poor reliability. Finally, 19 PL

reach direction inertial sensor derived variables

demonstrated excellent reliability, 14 had good

reliability, 2 possessed fair reliability, while 1 had

poor reliability.

4 DISCUSSION

The primary aim of this study was to determine the

inter-session test-retest reliability of the inertial

sensor derived measures of balance performance,

captured during the YBT. The findings of this

laboratory study indicate that the quantified YBT can

provide a reliable measure of balance performance,

laying the groundwork for its future use in clinical

practice.

The traditional analogue reach distances

demonstrated excellent test-retest reliability for the

ANT reach direction (ICC = 0.92) and good reliability

for the PM (ICC 0.74) and PL (ICC = 0.72) reach

directions. Previous research has demonstrated the

excellent test-retest reliability (ICC = 0.85-0.93) of

the YBT reach distances over a 48-hour period, using

multiple raters (Shaffer et al., 2013). To the best of

the authors’ knowledge, this is the first study to

present inter-session test-retest reliability of the YBT

reach directions, using a single rater. While the

reliability results for the PM and PL reach directions

presented in this study are lower than that of Shaffer

and colleagues (Shaffer et al., 2013), the time frame

between testing time-points is significantly shorter

(48-hours) than that used in this study (1 week). This

longer follow-up period would likely increase the

amount of within-subject variance between testing

points, potentially explaining the lower ICC scores

for the PM and PL reach directions.

When comparing the inertial sensor derived

variables and the traditional YBT reach distances, 12

ANT variables demonstrated excellent test-retest

reliability (ICC > 0.75), comparable to the reliability

of the traditional reach distance (Table 2).

Importantly, when considering the PM and PL reach

directions, 14 (PM) and 19 (PL) inertial sensor

variables demonstrated excellent test-retest

reliability, superior to the good reliability

demonstrated by the traditional analogue reach

distances. This is of note as the YBT is the current

clinical standard in dynamic balance assessment,

specifically used as an objective outcome measure in

sports medicine populations (Smith et al., 2015,

Plisky et al., 2006, Gribble et al., 2012). Importantly,

the results presented in this reliability study

demonstrate that the inertial sensor quantified YBT

can provide a comparable level of measurement

reliability for the ANT reach direction, and superior

reliability for the PM and PL reach directions.

Furthermore, these 45 quantified variables with

excellent reliability are capable of quantifying

different aspects of balance control and strategy

leveraged by an individual during the YBT, allowing

clinicians and researchers to capture detailed

biomechanical information pertaining to balance

performance during the YBT, outside of the

laboratory setting.

Four variables, gyro x RMS, gyro y AUC FFT,

gyro mag RMS and gyro mag AUC FFT, consistently

provided excellent reliability across all three reach

directions. However, when considering the PM and

PL reach directions alone, it was seen that 11 of the

same inertial sensor derived variables possessed

excellent levels of test-retest reliability. One possible

explanation for the high level of consistency between

the PM and PL directions, when compared with the

ANT direction, is the different movement strategies.

icSPORTS 2018 - 6th International Congress on Sport Sciences Research and Technology Support

Table 1: Mean (SD) for the different YBT variables for the two testing time points.



ANT PM PL



Week1 Week2 Week1 Week2 Week1 Week2

ReachDistance 56.8(5.2) 56.5(5.4) 99.7(7.3) 100.4(7.3) 97.7(7) 98.9(7.8)

95EV 365.8(399.7) 380.0(354.3) 369.6(295.4) 459.3(452.3) 504.9(482.9) 485.8(440.9)

GyroX

RMS 7.08(3.3) 6.3(2.4) 17.4(4.9) 18.2(5.5) 17.3(5.4) 18.2(6.2)

SEn 1.4(0.4) 1.4(0.4) 0.5(0.2) 0.5(0.2) 0.5(0.2) 0.5(0.2)

AUCFFT 19.9(7.6) 18.8(6.3) 27.5(11.1) 28.1(10.8)

 27.2(11) 27.1(10.5)

Variance 61.4(65.4) 45.1(38.7) 331.6(187) 363204.3 332.2(198.2) 372.5(233.9)

GyroY

RMS 11.3(3.8) 11.5(4.2) 8.9(2.5) 9.2(2.9) 10.6(4.1) 10.5(3.5)

SEn 1.0(0.3) 0.9(0.3) 1.2(0.3) 1.1(0.3) 1.1(0.3) 1(0.3)

AUCFFT 27.0(10.3) 27(10)

22.7(8.5) 22.8(8.4) 25.3(10.8) 25.4(9.7)

Variance 143.4(97.2) 150.8(107.2) 86.2(51.6) 92.1(59.7) 124.4(92.1) 120.9(78.4)

GyroZ

RMS 5.3(2.0) 4.8(1.7) 6.8(2.6) 6.8(2.1) 10.4(2.6) 10.2(2.9)

SEn 1.4(0.3) 1.5(0.3) 1.2(0.3) 1.1(0.3) 0.8(0.2) 0.8(0.3)

AUCFFT

 16.9(6.3) 16(5.5) 17.3(6.9) 16.7(5.7) 19.9(7.8) 18.7(6.9)

Variance 33.4(24.0) 26.1(17.7) 54.3(46.6) 51.7(33.8) 114.2(56.1) 112.1(63.3)

GyroMag

RMS 14.7(4.7) 14.2(4.5) 20.9(5.5) 21.7(5.9) 23.1(6.5) 23.6(7.1)

SEn 1.2(0.3) 1.2(0.3) 0.8(0.2) 0.7(0.2) 0.8

(0.3) 0.7(0.3)

AUCFFT 25.4(9.2) 25.2(9.3) 26.9(10.4) 27.7(9.9) 28.2(10.6) 29.3(11.1)

Variance 79.5(50.6) 74(48.6) 152.8(87) 172.3(88.6) 198.6(115.1) 228.1(152.4)

AccelX

RMS 0.9(0.7) 1.9(3.2) 1.2(0.5) 2.5(3.3) 2.1(0.6) 2.9(2.1)

SEn 1.5(0.3) 1.5(0.4) 1.6

(0.4) 1.5(0.3) 0.8(0.2) 0.8(0.2)

AUCFFT 1.9(0.7) 2.2(1.2) 1.6(0.5) 2(1) 2.4(0.8) 2.6(1)

Variance 0.4(0.3) 0.4(0.3) 0.4(0.3) 0.4(0.2) 2.1(0.8) 2.1(0.9)

AccelY

RMS 9.3(0.4) 11.2(4.8) 7.5(0.8) 9.5(5.5) 7.2(0.9) 9.2(5.6)

SEn

1.3(0.4) 1.7(0.3) 0.7(0.3) 0.9(0.6) 0.6(0.3) 0.7(0.6)

AUCFFT 3.4(1.0) 4.1(2) 3.1(0.9) 3.3(1.1) 3.1(0.9) 3.2(1.1)

Variance 0.2(0.1) 0.3(0.4) 2.5(1.5) 2.2(1.6) 3.2(2.2) 3(2.4)

AccelZ

RMS 3.1(1.1) 2.7(1.3) 6.3(1) 6.1(1) 6.4

(1) 6.3(0.9)

SEn 1.3(0.4) 1.4(0.5) 0.5(0.1) 0.4(0.1) 0.6(0.2) 0.5(0.2)

AUCFFT 2.3(0.8) 2.1(0.8) 3.5(1.1) 3.4(0.9) 3.2(1) 3.2(1)

Variance 0.6(0.8) 0.5(0.5) 4(1.6) 4.3(1.5) 3.1(1.5) 3.4(1.7)

AccelMag

RMS 9.9(0.2) 11.9(5.4)

9.9(0) 12(5.6) 9.9(0) 11.9(5.3)

SEn 1.8(0.3) 1.8(0.4) 2(0.3) 1.8(0.4) 1.9(0.3) 1.8(0.4)

AUCFFT 3.5(1.0) 4.1(1.7) 3(1) 3.3(1.6) 2.8(1) 3(1.4)

Variance 0.2(0.1) 0.2(0.2) 0.1(0.1) 0.1(0.1) 0.1(0.1) 0.1(0.1)

Pitch Range 13.1

(5.7) 10.9(4.7) 39.9(8) 40.7(7.5) 44.9(12) 46.3(13.3)

Roll Range 10.6(4.8) 8.7(3.5) 15.4(3.7) 16.5(5.6) 19.7(4.8) 18.3(4.5)

Yaw Range 19.6(6.8) 19.1(6.6) 22.7(6) 21.1(7.6) 26.7(5.6) 27.4(7.3)

Inter-session Test-retest Reliability of the Quantiﬁed Y Balance Test

Table 2: ICC and 95% CI for the traditional and inertial sensor derived YBT variables.

ANT PM PL

ICC LB UB ICC LB UB ICC LB UB

Reach Distance 0.92 0.84 0.96 0.74 0.54 0.87 0.72 0.50 0.85

95EV 0.62 0.33 0.80 0.86 0.71 0.93 0.73 0.51 0.86

Gyro X

RMS 0.76 0.54 0.88 0.82 0.66 0.91 0.78 0.59 0.88

SEn 0.82 0.66 0.91 0.64 0.36 0.81 0.71 0.44 0.85

AUC FFT 0.74 0.54 0.86 0.81 0.64 0.90 0.81 0.65 0.90

Variance 0.70 0.45 0.84 0.80 0.63 0.90 0.75 0.55 0.87

Gyro Y

RMS 0.86 0.72 0.93 0.67 0.42 0.82 0.79 0.60 0.89

SEn 0.80 0.62 0.90 0.65 0.40 0.81 0.78 0.58 0.89

AUC FFT 0.76 0.56 0.88 0.82 0.67 0.91 0.79 0.60 0.89

Variance 0.87 0.75 0.93 0.65 0.40 0.81 0.71 0.48 0.85

Gyro Z

RMS 0.65 0.39 0.81 0.70 0.47 0.84 0.73 0.51 0.86

SEn 0.66 0.41 0.82 0.64 0.39 0.81 0.77 0.59 0.88

AUC FFT 0.66 0.41 0.82 0.71 0.49 0.85 0.74 0.53 0.86

Variance 0.58 0.30 0.77 0.64 0.38 0.81 0.69 0.45 0.83

Gyro Mag

RMS 0.86 0.73 0.93 0.82 0.66 0.91 0.77 0.59 0.88

SEn 0.66 0.41 0.82 0.69 0.42 0.85 0.69 0.41 0.84

AUC FFT 0.79 0.60 0.89 0.81 0.65 0.90 0.78 0.59 0.88

Variance 0.84 0.70 0.92 0.79 0.61 0.89 0.70 0.48 0.84

Accel X

RMS 0.01 -0.30 0.34 0.08 -0.22 0.40 0.10 -0.21 0.41

SEn 0.65 0.39 0.81 0.64 0.38 0.80 0.75 0.54 0.87

AUC FFT 0.42 0.11 0.67 0.54 0.24 0.75 0.82 0.67 0.91

Variance 0.92 0.83 0.96 0.51 0.21 0.73 0.91 0.82 0.95

Accel Y

RMS 0.74 0.44 0.88 0.71 0.47 0.86 0.72 0.48 0.86

SEn 0.52 0.19 0.74 0.77 0.55 0.88 0.66 0.40 0.83

AUC FFT 0.47 0.13 0.71 0.86 0.72 0.93 0.83 0.66 0.92

Variance 0.09 -0.29 0.44 0.88 0.75 0.94 0.87 0.74 0.94

Accel Z

RMS 0.68 0.42 0.84 0.74 0.53 0.86 0.71 0.48 0.85

SEn 0.62 0.36 0.80 0.62 0.32 0.80 0.56 0.26 0.76

AUC FFT 0.46 0.14 0.69 0.76 0.57 0.88 0.76 0.56 0.88

Variance 0.69 0.45 0.83 0.68 0.45 0.83 0.65 0.40 0.81

Accel Mag

RMS 0.38 0.01 0.66 0.74 0.53 0.86 0.78 0.58 0.89

SEn 0.51 0.17 0.74 0.62 0.32 0.80 0.68 0.42 0.84

AUC FFT 0.67 0.41 0.83 0.76 0.57 0.88 0.85 0.70 0.93

Variance 0.58 0.28 0.78 0.68 0.45 0.83 0.84 0.68 0.92

Pitch Pitch 0.67 0.29 0.85 0.78 0.58 0.89 0.81 0.63 0.91

Roll Roll 0.77 0.52 0.89 0.47 0.14 0.71 0.43 0.09 0.69

Yaw Yaw 0.87 0.73 0.94 0.24 -0.14 0.56 0.70 0.46 0.85

The ANT reach predominantly requires sagittal plane

movements, while the PM and PL reach directions

both require more complex multi-planar movement

(Kang et al., 2015). As a result, the variables that

demonstrated excellent reliability when quantifying

the single planar ANT direction (13 variables) are

distinctly different to those that possessed excellent

reliability when quantifying the multi-planar PM/ PL

reach directions (11 variables).

The results presented in this paper build on

previous research which has demonstrated the intra-

session test-retest reliability and the discriminant

validity of the quantified YBT (Johnston et al.,

2017b). This past work demonstrated that the within-

session test-retest reliability of the inertial sensor

quantified YBT ranged from an ICC of 0.76-0.92 for

the 95EV measure, depending on the reach direction

(Johnston et al., 2017b). While the intra-session

reliability results presented are higher than the inter-

session reliability results presented in this study, the

longer follow-up leveraged in the inter-session study

likely increased the amount of within-subject

variance. As such, when the findings of this study are

viewed in conjunction with those of the previous

studies, it becomes clear that the quantified YBT can

be considered a valid and reliable measure of

dynamic balance performance. This has major

significance as it lays the ground work for the

implementation of this system in clinical populations,

potentially aiding the identification of individuals at

icSPORTS 2018 - 6th International Congress on Sport Sciences Research and Technology Support

risk of injury/ disease and tracking recovery and

response to intervention.

While no research has determined the inter-

session test-retest reliability of the quantified YBT,

previous work has established the reliability of other

inertial sensor quantified clinical assessments. Simon

and colleagues (2017) demonstrated that an inertial

sensor derived measure of static balance performance

during the balance error scoring system, obtained

from a lumbar worn iPad, possessed good – excellent

1-week test-retest reliability. Similarly, McGrath and

colleagues (2011) demonstrated that 18 inertial

sensor derived variables obtained during the timed up

and go test possessed excellent test-retest reliability,

over a 4-week period. As such, the findings presented

in this paper contribute to the body of evidence that

inertial sensor quantified clinical assessments can

provide a reliable measure of motor performance.

There are a number of contextual factors that need

to be considered related to this study. Firstly, the

population recruited as part of this study is a young

healthy adult population, aged between 18-40. As

such, these findings may not be generalisable across

different populations. Further research is required to

investigate the inter-session test-retest reliability

across various populations, including clinical and

sporting populations. Secondly, an important

characteristic of this study was the 1-week test-retest

design. The 1-week follow-up period used in this

study was chosen to ensure an adequate washout

period between tests, while reducing the likelihood

that individuals may suffer any injuries or illnesses

which may have impaired their balance between

testing points. This 1 week follow-up period is

consistent with other sensor based balance

assessment inter-session reliability studies in the

literature (Simon et al., 2017, Amick et al., 2015). As

such, the results of this study are promising as they

demonstrated the good-excellent reliability of a large

proportion of the quantified YBT variables.

5 CONCLUSION

The results of this inter-session test-retest reliability

study demonstrate that the quantified YBT, as

instrumented by a single lumbar inertial sensor, can

provide a reliable measure of balance performance,

across all three reach directions. Furthermore, a large

proportion of the quantified variables demonstrated

similar or superior reliability to the traditional

analogue YBT reach distances. As such, this study

lays the groundwork for future work investigating the

utility of the quantified YBT as a digital biomarker of

injury/ disease risk, recovery, and response to

intervention. Further research is required to

investigate the reliability of this measure across

clinical and sporting populations.

ACKNOWLEDGEMENTS

Funding for this study was provided by the Science

Foundation of Ireland (12/RC/2289).

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