Measurement of Lower Limb Joint Kinematics using Inertial Sensors During Stair Ascent and Descent in Healthy Older Adults and Stroke Survivors
Bibliographic record
Abstract
This study validated the feasibility of inertial sensors in estimating lower limb joint kinematics during stair ambulation in healthy older adults and stroke survivors. Three dimensional motion data were collected using an inertial sensor-based system from 9 persons with stroke and 9 healthy older adults as they ascended and descended a staircase at a self-selected pace. The measured joint angles were compared with a laboratory-based motion capture system by computing differences in range of motion (RoM), grand mean error, standard deviation, and coefficients of multiple correlations. For stroke survivors, differences in RoM measurements between these two systems were determined to be 3.3 ± 8.1°, while the highest correlations were found in the estimation of sagittal plane joint angles after offset correction. Results suggest that the inertial sensor system is suitable for estimating major joint angles in healthy older adults as well as the RoM for stroke survivors. New calibration procedures are necessary for applying the technology to a stroke population.
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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 | 0.000 | 0.002 |
| 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 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".