Validity of using wearable inertial sensors for assessing the dynamics of standing balance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Observational balance tests (e.g., Berg Balance Scale) are used to evaluate fall-risk. However, they tend to be subjective, and their reliability and sensitivity can be limited. The use of in-lab equipment for objective balance evaluation has not been common in clinical practice, due to the requirement of an equipped lab space. While inertial measurement units (IMUs) enable objective out-of-lab balance assessment, their accuracy has not been validated. This study aims to investigate the accuracy of IMUs against in-lab equipment for characterizing standing balance. Ten non-disabled individuals participated in a two-minute standing test on a force-plate. Four approaches were used for estimating inter-segmental moments and center of pressure (COP) position in a four-segment model: (1) camera-based bottom-up approach; (2) camera-based top-down approach; (3) IMU-based (accelerometer) top-down approach; and (4) IMU-based (accelerometer and gyroscope) top-down approach. Approaches 2 to 4 resulted in high accuracy compared to the reference, Approach 1. The root-mean-square errors in estimating the segments' orientation, ground reaction forces, COP position, and joint moments were smaller than 0.3°, 0.2 N/kg, 1.5 mm, and 0.016N·m/kg, respectively. Since no significant differences were observed between the accuracy of Approaches 3 and 4, only accelerometer recordings are needed and could be recommended for monitoring standing balance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it