Feasibility and safety study of wearable cyborg Hybrid Assistive Limb for pediatric patients with cerebral palsy and spinal cord disorders
Bibliographic record
Abstract
Introduction The wearable cyborg Hybrid Assistive Limb (HAL) is the world’s first cyborg-type wearable robotic device, and it assists the user’s voluntary movements and facilitates muscle activities. However, since the minimum height required for using the HAL is 150 cm, a smaller HAL (2S size) has been newly developed for pediatric use. This study aimed to (1) examine the feasibility and safety of a protocol for treatments with HAL (2S size) in pediatric patients and (2) explore the optimal method for assessing the efficacy of HAL. Methods This clinical study included seven pediatric patients with postural and motor function disorders, who received 8–12 sessions of smaller HAL (2S size) treatment. The primary outcome was the Gross Motor Function Measure-88 (GMFM-88). The secondary outcomes were GMFM-66, 10-m walk test, 2- and 6-min walking distances, Canadian Occupational Performance Measure (COPM), a post-treatment questionnaire, adverse events, and device failures. Statistical analyses were performed using the paired samples t-test or Wilcoxon signed-rank test. Results All participants completed the study protocol with no serious adverse events. GMFM-88 improved from 65.51 ± 21.97 to 66.72 ± 22.28 (p = 0.07). The improvements in the secondary outcomes were as follows: GMFM-66, 53.63 ± 11.94 to 54.96 ± 12.31, p = 0.04; step length, 0.32 ± 0.16 to 0.34 ± 0.16, p = 0.25; 2-MWD, 59.1 ± 57.0 to 62.8 ± 63.3, p = 0.54; COPM performance score, 3.7 ± 2.0 to 5.3 ± 1.9, p = 0.06; COPM satisfaction score, 3.3 ± 2.1 to 5.1 ± 2.1, p = 0.04. Discussion In this exploratory study, we applied a new size of wearable cyborg HAL (2S size), to children with central nervous system disorders. We evaluated its safety, feasibility, and identified an optimal assessment method for multiple treatments. All participants completed the protocol with no serious adverse events. This study suggested that the GMFM would be an optimal assessment tool for validation trials of HAL (2S size) treatment in pediatric patients with posture and motor function disorders.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".