Balance Assessments Using Smartphone Sensor Systems and a Clinician-Led Modified BESS Test in Soccer Athletes with Hip-Related Pain: An Exploratory Cross-Sectional Study.

backgroundThe Balance Error Scoring System (BESS) is the most practiced static postural balance assessment tool, which relies on visual observation, and has been adopted as the gold standard in the clinic and field. However, the BESS can lead to missed and inaccurate diagnoses-because of its low inter-rater reliability and limited sensitivity-by missing subtle balance deficits, particularly in the athletic population. Smartphone technology using motion sensors may act as an alternative option for providing quantitative feedback to healthcare clinicians when performing balance assessments. The primary aim of this study was to explore the discriminative validity of an alternative novel smartphone-based cloud system to measure balance remotely in soccer athletes with and without hip pain.

methodsThis is an exploratory cross-sectional study. A total of 64 Australian soccer athletes (128 hips, 28% females) between 18 and 40 years completed single and tandem stance balance tests that were scored using the modified BESS test and quantified using the smartphone device attached to their lower back. An Exploratory Factor Analysis (EFA) and a Clustered Receiver Operating Characteristic (ROC) using an Area Under the Curve (AUC) were used to explore the discriminative validity between the smartphone sensor system and the modified BESS test. A Linear Mixed-Effects Analysis of Covariance (ANCOVA) was used to determine any statistical differences in static balance measures between individuals with and without hip-related pain.

resultsEFA revealed that the first factor primarily captured variance related to smartphone measurements, while the second factor was associated with modified BESS test scores. The ROC and the AUC showed that the smartphone sway measurements in the anterior-posterior and mediolateral directions during single-leg stance had an acceptable to excellent level of accuracy in distinguishing between individuals with and without hip-related pain (AUC = 0.72-0.80). Linear Mixed-Effects ANCOVA analysis found that individuals with hip-related pain had significantly less single-leg balance variability and magnitude in the anteroposterior and mediolateral directions compared to individuals without hip-related pain (

conclusionDue to the ability of smartphone technology to discriminate between individuals with and without hip-related pain during single-leg static balance tasks, it is recommended to use the technology in addition to the modified BESS test to optimise a clinician-led assessment and to further guide clinical balance decision-making. While the study supports smartphone technology as a method to assess static balance, its use in measuring balance during dynamic movements needs further research.