Gait parameters assessed with inertial measurement unit during 6-minute walk test in people after stroke
Bibliographic record
Abstract
Gait impairments are among the main issues for stroke survivors as they are often linked with a lack of endurance capacity, balance impairments and functional limitations. These conditions can be carefully assessed by combining an endurance capacity test, the 6-minute walk test (6MWT), with the analysis of gait performed by an inertial measurement unit (IMU). We investigated the evolution of gait spatiotemporal and kinematic parameters during the 6MWT and compared it with age-matched healthy subjects. Moreover, gait parameters and 6MWT distance were associated with clinical outcome scales. In a postacute rehabilitation general hospital, we performed an observational study. Subjects with a single cortical stroke were recruited into the stroke group (SG). An age-matched healthy group (HG) was also recruited. All participants performed a 6MWT while wearing an IMU. The outcomes considered were 6MWT distance, gait spatiotemporal and kinematic parameters, and symmetry. Before the test at each subject, in the SG was administered Berg balance scale, Canadian neurological stroke scale and motricity index. 32 subjects were recruited into the SG, and 12 into the HG. Between the paretic and nonparetic limbs of the SG, there were differences in the stance phase and single support phase (P < 0.05). SG gait speed and stride length strongly correlated with balance, strength and disability scales. The SG walked fewer meters than the HG (Δ = -260.90 m; P < 0.001). Adopting an IMU during a 6mwt resulted valuable and effective in providing meaningful information regarding both the disability and functional capabilities of SG subjects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".