Athletic Training and Sports Health Care

Original Research 

Comparison of the SWAY Balance Mobile Application to the Abbreviated Balance Error Scoring System

Ryan Z. Amick, PhD; Samantha D. Jansen, MA; Alex Chaparro, PhD; Nils A. Hakansson, PhD; Jeremy A. Patterson, PhD, FACSM, ECP; Michael J. Jorgensen, PhD

Abstract

The SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) is a new method for quantifiably assessing balance in both clinical and on-field environments. The purpose of this study was to compare the accelerometer-based SWAY balance assessment to the commonly used and observation-based Abbreviated Balance Error Scoring System (BESS) balance assessment. Forty-four participants (22 male; mean age: 19.59 ± 1.23 years) completed the SWAY Balance Mobile Application protocol while the Abbreviated BESS was simultaneously scored. Bivariate linear regression was performed and correlation co-efficient calculated to determine the degree of correlation between the SWAY and Abbreviated BESS scores. The mean Abbreviated BESS score was 5.93 ± 4.45 and the mean SWAY score was 81.79 ± 14.06. A significant negative correlation was found between the two balance measures (r = −0.601, P < .0001). The SWAY balance assessment may provide for a means to quantifiably assess balance in an objective manner, thereby eliminating subjective bias in balance assessments. [Athletic Training & Sports Health Care. 2015;7(3):89–96.]

From the Departments of Human Performance Studies (RZA, JAP), Psychology (AC, SDJ), and Biomedical Engineering (NAH, MJJ), Wichita State University, Wichita, Kansas.

The authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Ryan Z. Amick, PhD, Department of Human Performance Studies, Wichita State University, 1845 Fairmount, Wichita, KS 67260-0016. E-mail: ryan.amick@wichita.edu

Received: October 28, 2014
Accepted: February 18, 2015

Abstract

The SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) is a new method for quantifiably assessing balance in both clinical and on-field environments. The purpose of this study was to compare the accelerometer-based SWAY balance assessment to the commonly used and observation-based Abbreviated Balance Error Scoring System (BESS) balance assessment. Forty-four participants (22 male; mean age: 19.59 ± 1.23 years) completed the SWAY Balance Mobile Application protocol while the Abbreviated BESS was simultaneously scored. Bivariate linear regression was performed and correlation co-efficient calculated to determine the degree of correlation between the SWAY and Abbreviated BESS scores. The mean Abbreviated BESS score was 5.93 ± 4.45 and the mean SWAY score was 81.79 ± 14.06. A significant negative correlation was found between the two balance measures (r = −0.601, P < .0001). The SWAY balance assessment may provide for a means to quantifiably assess balance in an objective manner, thereby eliminating subjective bias in balance assessments. [Athletic Training & Sports Health Care. 2015;7(3):89–96.]

From the Departments of Human Performance Studies (RZA, JAP), Psychology (AC, SDJ), and Biomedical Engineering (NAH, MJJ), Wichita State University, Wichita, Kansas.

The authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Ryan Z. Amick, PhD, Department of Human Performance Studies, Wichita State University, 1845 Fairmount, Wichita, KS 67260-0016. E-mail: ryan.amick@wichita.edu

Received: October 28, 2014
Accepted: February 18, 2015

Balance is a complex and multi-dimensional process that allows for the maintenance of a specific posture, or postures, while executing any number of different tasks. These tasks can vary from simple activities of daily living such as sitting upright or quiet standing to more complex skilled activities executed while performing work duties or recreational activities. Our ability to perform this wide range of activities is dependent on our capacity to coordinate and control various components of multiple intrinsic systems that contribute to the process of maintaining balance.1 These include biomechanical, motor, and sensory components that are further influenced by task demands, environmental constraints, and individual capabilities.1–5

Several different balance assessment techniques are currently available and widely used. These include both subjective and objective assessments. Subjective balance assessment methods vary in methodology and test complexity, ranging from quiet standing to more complex assessments that systematically remove or alter available sensory feedback.6 The benefits of most balance assessments of this type are that they can generally be administered in only a few minutes, require little to no equipment, and have no associated costs.

A commonly used subjective balance assessment method is the Balance Error Scoring System (BESS).7 The BESS is a clinical balance assessment using modified Romberg stances that are first performed on a non-compliant support surface, followed by a compliant foam surface. A modified version of the BESS assessment is also used by clinicians.8 This version, the Abbreviated BESS (A-BESS), requires the participant to perform the same balance stances as the original BESS, including bipedal stance, non-dominant single leg stance, and tandem stance with non-dominant foot in rear. However, this version removes the compliant foam support surface condition, only having participants perform the stances on a non-compliant solid support surface.9 This version of the BESS was originally designed to measure the balance component of the Sport Concussion Assessment Tool 2 (SCAT2)10,11; however, due to its ease of use it has come to be increasingly used as a stand-alone functional assessment, especially in the athletic community. It has additionally been stated that it is appropriate for use in non-athletic clinical settings.9 Scoring of the A-BESS is the same as for the traditional BESS, where a test administrator observes the participant and counts the number of pre-defined errors that occur (Table 1); however, here the maximum number of errors possible per stance is 10, giving a potential maximum score of 30.

Balance Error Scoring System (BESS) Scoring Errors

Table 1:

Balance Error Scoring System (BESS) Scoring Errors

Despite increasing use of these tests, both the BESS and A-BESS demonstrate some limitations. The primary limitation is that it is a subjective assessment, relying on the knowledge and experience of the test administrator to correctly identify and score the balance errors that occur in each trial. This reliance on purely observational scoring has the potential to introduce bias into the participants’ final balance score, increase the variability, and reduce the intra-rater and inter-rater reliability of the assessment.12 To address this, it has been recommended that multiple test administrators concurrently score each participant’s assessment, and then average those scores to determine the participant’s final overall score. However, this limits the practicality of the assessment as a clinical tool because multiple test administrators are rarely available for the assessment of a single participant. Additionally, it has been reported that the A-BESS may demonstrate a reduced ability to identify balance deficits when compared to the standard BESS, and may have a limited ability to identify balance improvements in those who already demonstrate good balance.9,13 Additionally, due to the subjective nature of the BESS and similar balance assessments, it may be more appropriate to assess balance through objective, technology-based techniques. This type of approach provides quantifiable outcomes without relying on a clinician’s subjective interpretation of a participant’s performance, which may reduce test reliability.

One potential method of quantifying patient postural stability is through accelerometry. Accelerometers are electromechanical sensors that produce an electrical output proportional to an acceleration input,14 and are capable of measuring accelerations associated with dynamic movement. Accelerometers have been shown to provide valid and reliable information for the assessment of balance and posture.15–17 Recent advances in micro-electromechanical systems (MEMS) have allowed for the physical size and cost of manufacturing of accelerometers to be reduced.18 Subsequently, MEMS accelerometers are now incorporated into many different mobile consumer electronic devices, such as smartphones, tablet computers, gaming systems, and other multimedia devices.

Recently, a new method for assessing standing balance was developed by SWAY Medical, LLC (Tulsa, OK). The SWAY Balance Mobile Application is a U.S. Food and Drug Administration-approved mobile device software application that, when installed on a mobile consumer electronic device, accesses the MEMS tri-axial accelerometer output to assess balance through a series of balance tests. This assessment method is intended to provide professionals in various healthcare fields the ability to perform quantitative functional limitations assessments and fall risk assessments. Additionally, it can potentially be used by practitioners in sports medicine, such as athletic trainers, to provide supporting information to be used when making return-to-play decisions after an athlete has suffered an injury.

The SWAY balance test consists of five stances (Figure 1), including bipedal (feet together), tandem stance (left foot forward), tandem stance (right foot forward), single leg stance (right), and single leg stance (left). Each stance is performed on a firm surface with eyes closed for a period of 10 seconds. For the duration of each stance, the participant holds the measuring device upright against the mid-point of his or her sternum. Deflections of the tri-axial accelerometer, which arise in response to postural control and correction movements, are recorded throughout each of the balance test stances. On completion of the five stances, these deflections are used to calculate a final balance score ranging from 0 to 100, with higher scores indicating better balance. The units representing the balance score are interpretations of the acceleration of deflections within the accelerometers, and are calculated by undisclosed calculations from SWAY Medical, LLC.

SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) balance stances: (A) bipedal stance; (B) tandem stance left foot forward; (C) tandem stance right foot forward; (D) single leg stance right leg; (E) single leg stance left leg.

Figure 1.

SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) balance stances: (A) bipedal stance; (B) tandem stance left foot forward; (C) tandem stance right foot forward; (D) single leg stance right leg; (E) single leg stance left leg.

Preliminary testing has indicated that the SWAY balance test yields consistent and reliable measures of human standing balance. Pilot testing was performed comparing the consistency of SWAY balance scores to those measured concurrently with the BIODEX Balance System.19 Overall results showed no significant difference between mean stability scores recorded with the SWAY balance test and the BIODEX Balance System. Additionally, participant feedback was recorded with regard to the usability of the SWAY balance test. However, this study was limited to measuring posture only in the anterior-posterior directions. The rationale for this is that an early iteration of the SWAY platform was used, which had not yet incorporated accelerations detected in the medial-lateral direction. The current version of the SWAY software (version 1.6) now incorporates accelerations in all three axes for the calculation of a balance score.

Because of this change, a comparison of the SWAY balance test with commonly used balance assessments is warranted. Therefore, the objective of this study was to compare the SWAY Balance Mobile Application to the subjective and commonly used A-BESS. The rationale for this comparison was that the BESS has been shown to be a valid assessment of standing balance and was designed for use in both clinical and on-field environments.7,20–23 Results of this study may then yield evidence supporting the use of the SWAY balance test in the same environments.

Methods

Participants

Participants recruited for this study were a sample of convenience, and included NCAA Division I Track & Field athletes. The rationale for assessing a sample of this population was to compare the SWAY balance test to a subjective balance assessment technique that is commonly used to assess athletes. All methods and procedures received institutional review board approval and informed consent was received from all volunteer participants. Testing procedures were then explained to all participants and exclusion criteria confirmed verbally. Participants were excluded from participation if they reported any preexisting condition that may alter their ability to balance normally or met any of the exclusion criteria presented in Table 2. A total of 44 participants completed all testing (Table 3).

Participant Exclusion Criteria

Table 2:

Participant Exclusion Criteria

Participant Demographic Information

Table 3:

Participant Demographic Information

Demographic Information

For all participants, demographic information including date of birth, sex, and self-identified dominant leg were collected.

Anthropometric Measures

Several anthropometric variables were measured and recorded for each participant. Body mass was recorded using a digital scale (Zieis, Apple Valley, MN). Anthropometric measures were collected using a GPM calibrated anthropometer (Siber-Hegner, Zurich, Switzerland). Anthropometric measures recorded include standing height, height from floor of the suprasternal notch, height from floor of the xiphoid process, and height from floor of the third lumbar vertebrae as determined by palpation. Height from floor of the suprasternal notch and xiphoid process were averaged to determine the sternal mid-point. Standing height and weight were used to calculate each participant’s body mass index (BMI). For all measures, participants did not wear shoes.

Balance Assessments

Balance was assessed using the SWAY Balance Mobile Application and the A-BESS assessment method simultaneously. The SWAY balance test was administered using an Apple iPod Touch (Apple Computer Inc., Cupertino, CA) loaded with the SWAY Balance Mobile Application software (SWAY Medical, LLC). Participants were instructed to hold the device upright, using both hands to press the face of the device against the mid-point of their sternum, so that the top of the device was below a line horizontal with the clavicles. All participants first completed a familiarization trial, immediately followed by an experimental trial. Here, a trial is defined as the full completion of the SWAY protocol, which included five balance stances performed for a period of 20 seconds each. SWAY balance stances included bipedal standing (feet together), tandem standing (left foot forward), tandem standing (right foot forward), single leg standing (right), and single leg standing (left). On completion of each balance stance, instructions for the next balance stance were given on the device screen. All balance stances were performed on a solid surface without shoes and with eyes closed.

As participants progressed through the SWAY protocol, the balance stances that comprise the A-BESS, including bipedal standing, tandem standing with dominant foot forward, and non-dominant single leg standing, were also performed. As participants performed these stances, a certified athletic trainer with extensive experience in clinical functional assessment testing scored their performance using the BESS scoring criteria (Figure 1). However, to better reflect the SWAY testing position, the A-BESS assessment was modified to have participants hold their hands crossed along the mid-point of their sternum. This was to hold the SWAY measuring device in its recommended testing position. It was determined that this modification would not affect overall test performance. The A-BESS scoring criteria were subsequently modified to reflect the altered hand position where an error would be recorded if the participants removed their hands from their chest during the assessment. If the hands pull away from the chest, the SWAY device accelerometers detect the movement and account for it in the final SWAY balance score. For all conditions, participants were instructed to maintain the testing stance with their eyes closed and hands crossed across their chest.

Once all balance stances were completed, the SWAY device produced a final balance score ranging from 0 to 100, with a higher score indicating better balance. The units representing the balance score are interpretations of the acceleration of deflections within the accelerometers, and are calculated by undisclosed calculations from SWAY Medical, LLC. Additionally, the total number of observed errors committed during the A-BESS stances were summed to produce a final score, ranging from 0 to 30. A lower score indicated better balance.

Data Analysis

Statistical analysis for this study was completed with the use of SPSS version 21.0 software (SPSS, Inc., Chicago, IL) with a P value of less than .05 considered significant. A Kolmogorov–Smirnov test was performed to evaluate the A-BESS and SWAY scores for normality of distribution. For SWAY and A-BESS scores, an independent samples t test comparing the mean balance scores of male and female participants were calculated to determine whether mean balance sex differences exist. A bivariate linear regression model was performed to determine the coefficients of the slope and intercept, and standard error of the estimate. The Pearson product moment correlation coefficient (r) was calculated to determine the degree of correlation between the SWAY and A-BESS scores. The coefficient of determination (r2) was then calculated to determine the amount of shared variance between the SWAY and A-BESS scores.

Results

Participant demographic information is presented in Table 3. A-BESS and SWAY scores were found to be normally distributed. No significant sex differences were observed for the A-BESS (t = 0.639, P = .726) or the SWAY balance test (t = −1.573, P = .06). Descriptive statistics for each of the balance measures are reported in Table 4. The mean A-BESS score was 5.93 ± 4.45 and the mean SWAY score was 81.79 ± 14.06. Pearson product moment correlation coefficient (r) was calculated, where a significant negative correlation was found between the A-BESS and SWAY scores (r = −0.601, P < .0001). The SWAY balance score significantly predicted the A-BESS score (P < .0001), where the SWAY balance score accounted for 36.1% of the variance observed in the A-BESS score. A summary of the bivariate linear regression can be found in Figure 2.

Descriptive Statistics of Balance Measures

Table 4:

Descriptive Statistics of Balance Measures

Predicted Balance Error Scoring System (BESS) score against actual SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) balance score.

Figure 2.

Predicted Balance Error Scoring System (BESS) score against actual SWAY Balance Mobile Application (SWAY Medical, LLC, Tulsa, OK) balance score.

Discussion

As technology in consumer electronics has continued to advance, personal electronic devices such as smartphones, media players, and computers have begun to incorporate tri-axial accelerometers. The incorporation of tri-axial accelerometers allows for the increasing potential for the use of these personal electronic devices in the biomechanical analysis of balance, posture, and movement.19,24–29 Initial testing has shown that the accelerometers within mobile consumer electronic devices provide consistent and reliable outputs.19,30 In the current study, the SWAY Mobile Application was compared to the A-BESS assessment in a sample of NCAA Division I track athletes. The A-BESS assessment was chosen because it is a commonly used clinical field assessment that has been recommended for widespread use in sports.9,10 Additionally, normative data are available for performance classification and score comparison.9

When comparing A-BESS scores from this study to the normative data reported by Iverson and Koehle,9 we find that participants in this study performed slightly worse on the assessment than what may be expected. The mean A-BESS score for this study was 5.93 ± 4.45 errors, whereas normative data indicate the mean score for adults aged 20 to 29 years is 2.7 ± 2.5 errors. These authors further classify performance on the assessment as above average (0 errors), broadly normal (1 to 4 errors), below average (5 to 6 errors), poor (7 to 10 errors), and very poor (11+ errors).9 Therefore, participants in this study would generally be classified as having normal to below average performance. However, it is indicated that the presented normative data should be considered preliminary and may not be generalizable to the overall population.9 Additionally, the modification of the A-BESS in the current testing protocol further limits comparisons to reported normative values.

Despite the differences in A-BESS performance compared to normative data, the results of this study show a moderate correlation between the SWAY balance test and A-BESS assessments, which is statistically significant (r = −0.601, P < .001). This correlation is negative, reflecting the scoring paradigm of each of the respective tests. For the A-BESS assessment, a test participant begins with a score of 0 and the score increases as balance errors are observed. In this sense, an increasing score reflects poorer balance. Conversely, the SWAY balance assessment scores on a scale of 0 to 100. During the evaluation, deflections resulting from balance perturbations are recorded from the tri-axial accelerometer. As the final SWAY score is produced, a higher score indicates better balance.

The results here are consistent with previously reported work that compared the SWAY balance assessment protocol to the standard BESS assessment.31 In that study, a sample of non-athlete graduate and undergraduate students performed the SWAY balance test and BESS in a randomized order. These results showed that the mean BESS score was 10.4 ± 5.98 and the mean SWAY score was 79.62 ± 18.28. Additionally, a strong negative correlation, which is statistically significant, was found between these scores (r = −0.767, P < .01).31

Although both of these studies have found a significant correlation between the SWAY assessment and BESS assessment, the strength of associations fall within different levels of categorical interpretation.32 With regard to the previous study comparing the SWAY balance test to the standard BESS, the strength of association can be categorized as strong, whereas the current study found a moderate association. This variation in strength of association may be due to the differences between the standard BESS and the A-BESS. The A-BESS excludes the compliant floor condition used in the standard BESS; therefore, a participant’s balance control systems are not stressed in the same manner with the two assessments. Comparatively, although the SWAY balance test does not use a compliant floor condition, it does assess a participant’s balance on both dominant and non-dominant legs. Therefore, because participants are performing more balance tests (five instead of three) there is more opportunity for a perturbation to occur.

Although the primary finding of this study was that a statistically significant moderate correlation was found between the SWAY and A-BESS assessments, caution should be used when generalizing these findings. First, the data were obtained from a sample of healthy young adults. Therefore, the observed correlation may differ across other populations such as older adults and those with physical or physiological conditions affecting balance performance. Additionally, participants from this sample were all NCAA Division I track athletes. Therefore, results may not generalize to non-athletes of the same age group.

Implications for Clinical Practice

Advances in technology have greatly improved the ability to objectively and quantifiably measure balance through the use of tri-axial accelerometers installed in current mobile consumer electronic devices. The SWAY Balance Mobile Application shows significant correlation to the A-BESS, which may indicate the potential for the SWAY balance test to be used to assess balance in an athletic population. The advantages of using the mobile device based SWAY assessment for measuring balance are that it is mobile, uses mobile communications devices that are readily available, is relatively inexpensive, and is easy to use. Additionally, as opposed to many currently used clinical or field assessments, the SWAY assessment is objective and does not rely on the test administrators’ clinical knowledge or experience in interpreting a participant’s performance to produce a score. This tool could therefore provide medical professionals, physical education coaches, parents, and the athletic community a means to quantifiably assess balance in an objective manner.

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Balance Error Scoring System (BESS) Scoring Errors

Moving the hands off of the hips

Opening the eyes

Step, stumble, or fall

Hip flexion or abduction greater than 30°

Lifting the forefoot or heel off of the testing surface

Remaining out of testing position for more than 5 seconds

Participant Exclusion Criteria

Male or female younger than 18 years

Current illness

Medical history that includes:

Neurological dysfunction (including concussion) without full medical release

Current or previous musculoskeletal injury affecting balance

Uncorrected vision

Vestibular damage or disease

Current, unprescribed pharmacological intervention

Participant Demographic Information

CHARACTERISTICMEAN ± SDMAXIMUMMINIMUMMEDIAN
Overall (N = 44)
  Age (years)19.59 ± 1.2323.0018.0019.00
  Weight (kg)75.29 ± 15.60124.4053.7072.75
  Stature (cm)174.40 ± 12.78192.80116.90174.70
  BMI (kg/m2)24.88 ± 5.2645.4119.0823.23
  3rd lumbar vertebrae (cm)107.35 ± 5.48120.5095.60107.10
  Sternal mid-point (cm)132.03 ± 6.19145.10119.40132.08
Male (n = 22)
  Age (years)19.77 ± 1.3123.0018.0020.00
  Weight (kg)82.69 ± 15.36124.4063.0577.60
  Stature (cm)182.40 ± 6.48192.80172.00181.25
  BMI (kg/m2)24.82 ± 4.2235.8019.7923.96
  3rd lumbar vertebrae (cm)110.39 ± 4.99120.50104.00108.75
  Sternal mid-point (cm)136.23 ± 4.70145.10127.85135.70
Female (n = 22)
  Age (years)19.41 ± 1.1422.0018.0019.00
  Weight (kg)67.89 ± 12.17102.0053.7062.88
  Stature (cm)166.40 ± 12.58179.10116.90168.50
  BMI (kg/m2)24.94 ± 6.2445.4119.0822.45
  3rd lumbar vertebrae (cm)104.31 ± 4.14110.7095.60104.40
  Sternal mid-point (cm)127.82 ± 4.39135.75119.40127.60

Descriptive Statistics of Balance Measures

CHARACTERISTICMEAN ± SDMAXIMUMMINIMUMMEDIAN
Overall (N = 44)
  SWAY81.79 ± 14.0699.6052.0085.85
  BESS5.93 ± 4.4517.000.005.00
Male (n = 22)
  SWAY78.51 ± 15.1797.8053.2085.45
  BESS6.36 ± 4.4214.000.006.50
Female (n = 22)
  SWAY85.06 ± 12.3399.6052.0089.00
  BESS5.50 ± 4.5417.000.004.00

10.3928/19425864-20150422-04

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