The Efficacy of a Programmable Keyboard on Upper Limb Function and the Ability to Perform Activities of Daily Living in a Person with Hemiplegia: Case Report.
Bibliographic record
Abstract
INTRODUCTION: Studies on rehabilitation devices in individuals with hemiplegia have shown that robotic rehabilitation tends to be more effective in individuals with mild rather than moderate or severe hemiplegia. The aim of this study was to demonstrate the rehabilitative effectiveness of a programmable keyboard (Click4all®) in improving the performance of daily life activities (PC, tablet, and smartphone) in a 30-year-old man with hemiplegia. METHODS: A 31-year-old man underwent surgery in 2017 to remove prefrontal cortical dysplasia responsible for epileptic seizures. Following the operation, he developed left hemiplegia. Following this intervention, he developed left hemiplegia. The upper limb showed shoulder asymmetry in the frontal plane, with the arm extended along the trunk and the thumb slightly adducted. The patient was assessed three times using the following tools: Matching Person and Technology (MPT), Survey of Technology Use (SOTU), Assistive Technology Device Predisposition Assessment (ATD PA), and Quebec User Assessment of Satisfaction with Assistive Technology (QUEST 2.0). Following the initial assessment, the patient was trained to use Click4all® at home, applying it for 30 minutes per day over a period of two months. RESULTS: According to the MPT (ATD PA) rating scale, the patient reported satisfaction with the improvements achieved across various functional domains. The average score on the QUEST ranged from 4.62 to 4.25, showing that the patient was very satisfied with the aid. Finally, the patient's evaluation of adherence and performance indicated improvements in both the usability of the device and the residual function of the plegic limb over time. CONCLUSION: In this study, the Click4all® programmable keyboard was used to create a system comprising of both a rehabilitation and autonomy aid. The results highlighted not only an increased level of independence in the patient, but also a significant improvement in psychosocial well-being.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".