Early Recovery of Walking Ability in Patients After Total Knee Arthroplasty Using a Hip-Wearable Exoskeleton Robot: A Case-Controlled Clinical Trial
Bibliographic record
Abstract
INTRODUCTION: The Honda Walking Assist (HWA) is a hip-wearable exoskeleton robot for gait training that assists in hip flexion and extension movements to guide hip joint movements during gait. This study aimed to evaluate the effects of walking exercises with HWA in patients who underwent total knee arthroplasty (TKA). MATERIALS AND METHODS: This study involved 10 patients (11 knees) in the HWA group and 11 patients (11 knees) in the control group who underwent conventional physical therapy. The patients assigned to the HWA group underwent a total of 17-20 gait training sessions, each lasting approximately 20 min from week 1 to 5 following TKA. Self-selected walking speed (SWS), maximum walking speed (MWS), range of motion (ROM), knee extension and flexion torque, and Western Ontario and McMaster Universities Osteoarthritis Index subscales of pain (WOMAC-p) and physical function (WOMAC-f) scores were measured preoperatively, at 2, 4, and 8 weeks following TKA. RESULTS: Interventions were successfully completed in all patients, with no severe adverse events. A significant difference was noted in the time × group interaction effect between preoperative and week 2 SWS and MWS. Regarding knee function, there was a significant difference in the time × group interaction between preoperative and week 2 active ROM extension; however, no significant difference in knee torque, WOMAC-p, and WOMAC-f scores were observed. In the between-group post hoc analysis, WOMAC-f in the HWA group was higher than that in the control group at week 8. DISCUSSION: Although the control group showed a temporary reduction in SWS and MWS 2 weeks after TKA, the HWA group did not. These results suggest that HWA intervention promotes early improvement in walking ability after TKA. CONCLUSIONS: The gait training using HWA was safe and feasible and could be effective for the early improvement of walking ability in TKA patients.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".