Reliability of a New Test of Balance Function in Healthy and Concussion Populations
Bibliographic record
Abstract
Providing quantitative measures of balance and posture is a valuable aid in clinical assessment and in recent years several devices have been introduced that have demonstrated the accurate measure of balance via deviation of center of mass utilizing software algorithms and mobile devices. The purpose of this study was to assess the accuracy of EQ Balance against the SwayTM Balance System (Sway), another balance device that is currently established as an accurate measure of balance, and to evaluate the test–retest reliability of EQ Balance. Seventy individuals presenting to a sports medicine and concussion clinic volunteered to participate in the assessment of balance utilizing Sway and EQ Balance simultaneously. The group included 25 males and 45 females (mean age: 37.8 ± 14.8, range: 13–65) with and without concussion or other neurological conditions (39 concussed vs. 31 non-neurologically injured, or healthy). Twenty-six of the concussed participants were balance-impaired. Participants performed five postures while holding the mobile device against their chest. Participants held a device holder that secured two devices: one iPhone 6 with EQ Balance and a second iPhone 6 with Sway Balance. The average balance score on all five stances was recorded as the “average balance score”. Average balance scores were in statistical agreement between the two methods across the entire group, and for sub-groups according to the Deming regression (p < 0.01). The intra-class correlation (ICC) for the cohort was 0.87 (p < 0.001). Across the cohort, EQ Balance measured significantly worse balance scores in the balance-impaired group, comprised of participants with brain injury who failed a clinical balance screening test, compared to the group without clinically-determined balance impairment (this group includes healthy and some concussed patients). EQ Balance demonstrated safety, as it was considered safe to perform independently (i.e., without an observer) in those with impaired balance, and high test- retest reliability in the healthy and concussed patient population. Statistical agreement was established between the two measures of EQ Balance and Sway Balance for the average balance score across all five stances. The ICC analysis demonstrates strong consistency of the task output between test sessions. Given these results, EQ Balance demonstrates strength as a new balance assessment tool to accurately measure balance performance as part of a unique and novel gamified application in healthy and neurologically injured populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".