Development and feasibility of a modified Fugl-Meyer lower extremity assessment for telerehabilitation: a pilot study
Bibliographic record
Abstract
BACKGROUND: The majority of stroke survivors experience motor impairment which benefits from rehabilitation treatment. Telerehabilitation, remote delivery of rehabilitation services, is a possible solution providing access to rehabilitation for stroke survivors living in rural areas or in situations like the COVID-19 pandemic where face-to-face treatment may be risky. However, valid and reliable motor impairment measures have not yet been established over a telerehabilitation platform. The Fugl-Meyer (FM) lower extremity assessment is widely used clinically and in research. Thus, the aim was to develop a modified FM for telerehabilitation (FM-tele) and assess the feasibility and preliminary agreement of FM-tele scores with the FM. METHODS: Three phases were employed: phase 1 development, phase 2 feasibility, and phase 3 preliminary agreement. Literature review and consultation with clinicians were employed to develop the FM-tele. Community-dwelling individuals with stroke and FM evaluators were consulted to provide feedback via questionnaires on the feasibility of the FM-tele. To assess the preliminary agreement of the FM-tele, individuals with stroke participated in two sessions, one in-person and one via telerehabilitation. The standard version of the FM was administered during the in-person session. The FM-tele was administered in both sessions. RESULTS: From phase 1, clinician consultation identified the following key principles: safety of the client, clear lower extremity visualization, and minimization of position changes which guided FM-tele development (n = 7). Feasibility was established in phase 2 where participants with stroke indicated that they felt safe and experienced ease following the standardized instructions, despite some technological concerns (n = 5). FM evaluators agreed that participants were safe and indicated effective standardized instructions. Phase 3 (n = 5) indicated preliminary agreement of the FM-tele compared with the FM. CONCLUSIONS: Participants with stroke and clinical consultation indicated the FM-tele developed for telerehabilitation is feasible. A lower extremity motor assessment tool for telerehabilitation is urgently needed for stroke survivors living in rural areas or when face-to-face visits are impossible. This pilot study provides preliminary support for a future study.
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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 | 0.033 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".