Neurotechnology-Based, Intensive, Supplementary Upper-Extremity Training for Inpatients With Subacute Stroke: Feasibility Study
Bibliographic record
Abstract
Background: Upper-extremity hemiparesis is a common and debilitating impairment after stroke, severely restricting stroke survivors' ability to participate in daily activities and function independently. Alarmingly, only a small percentage of stroke patients fully recover upper extremity function. Animal models indicate that high-dose upper extremity training during the early poststroke phase can significantly enhance motor recovery. However, translating such programs for human patients remains challenging due to resource limitations, patient compliance issues, and administrative constraints. Objective: This study aimed to assess the feasibility and potential efficacy of an intensive, video game-based upper-extremity training protocol designed to improve movement quality during inpatient stroke rehabilitation. Additionally, it evaluated the resources required for this intervention. Specifically, the protocol provides high-intensity, high-dose training to facilitate motor recovery by engaging patients in targeted interactive exercises. Methods: Twelve patients with upper-extremity hemiparesis completed a 4-week intensive training program comprising 40 sessions of 60 minutes; the training was conducted for 2 hours per day, 5 days per week. This was delivered in addition to standard care, which included 3 therapeutic sessions daily. Two video game-based platforms were used: one platform (tech 1) targeted proximal movements involving the shoulder and elbow, while the second platform (tech 2) emphasized distal movements of the wrist and fingers. Feasibility was assessed using the measure of time on task and measures of patients' motivation and engagement. Potential effectiveness was assessed using the Fugl-Meyer Assessment of the upper extremity (FMA-UE) scale, Action Research Arm Test (ARAT), and Stroke Impact Scale (SIS). Results: Of the 12 patients, 8 completed the full protocol, 3 completed 34-38 sessions, and 1 completed 27 sessions. On average, patients actively engaged in exercises for 35 (SD 4) minutes per hour on the proximal platform (tech 1) and 37 (SD 2) minutes on the distal platform (tech 2). Patients reported high motivation and enjoyment throughout the sessions, with an Intrinsic Motivation Inventory enjoyment score of 6.49 (SD 0.66) out of 7. Pain levels were minimal, with a visual analogue scale (VAS) mean score of 2.00 (SD 2.32). Significant improvements were observed in motor function assessments: the mean improvement in FMA-UE score was 16.5 (SD 10.2) points, ARAT scores increased by 22.9 (SD 13.1) points, and the SIS Hand Function and Recovery score showed a mean delta of 1.23 (SD 0.80) points and a 23.33% (SD 21.5%) improvement, respectively. Conclusions: These findings demonstrate that a high-dose, high-intensity, video game-based training protocol is feasible and can be successfully integrated into subacute stroke rehabilitation. Additionally, preliminary evidence suggests that this supplementary intervention may be effective in enhancing motor recovery. This approach holds promise for future stroke rehabilitation protocols by offering an engaging, high-dose, and high-intensity program during early recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".