Estimation of 2-D Center of Mass Movement During Trunk Flexion–Extension Movements Using Body Accelerations
Bibliographic record
Abstract
Motions of the center of body mass (COM) and body segment acceleration signals are commonly used to indicate movement performance and stability during standing activities. The COM trajectory is usually calculated by video motion analysis, which has a time consuming setup and also is not readily available in all clinical settings. In this paper, we present a novel method to estimate the COM trajectory from the upper and lower limb accelerations, based on experimental data. We have modeled the relationships that exist between the 2-D hip and trunk acceleration data with the 2-D COM trajectory in the sagittal plane, during four trunk flexion-extension movement tasks and estimated the COM trajectory based on that model. The model accounted for between 93 +/- 9% to 97 +/- 3% of the resultant COM trajectory's variability, depending on the task. This corresponded to a range of absolute error between the true and estimated COM trajectories of 0.65 +/- 0.62 to 1.07 +/- 1.13 cm. The advantage of this model compared to our previous work on COM trajectory estimation is that it does not require any calibration and provides a reasonably accurate estimation of the COM trajectory, which can be used to study human balance performance in any clinical setting.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".