Electroencephalographic Changes of Brain Oscillatory Activity After Upper Limb Somatic Sensation Training in a Patient With Somatosensory Deficit After Stroke
Bibliographic record
Abstract
The development of an innovative functional assessment procedure based on the combination of electroencephalography (EEG) and robot-assisted upper limb devices may provide new insights into the dynamics of cortical reorganization promoted by rehabilitation. The aim of this study was to evaluate changes in event-related synchronization/desynchronization (ERS/ERD) in alpha and beta bands in a patient with pure sensory stroke who underwent a specific rehabilitation program for somatic sensation recovery. A 49-year-old, right-handed woman (time since stroke, 12 months) with severe upper limb somatic sensation deficits was tested using validated clinical scales and a standardized video-EEG system combined with the Bi-Manu-Track robot-assisted arm trainer protocol. The patient underwent a 3-month home-based rehabilitation program for promoting upper limb recovery (1 hour a day for 5 days a week). She was tested before treatment, at 1-month, and at 3-month during treatment. Results showed progressive recovery of upper limb function over time. These effects were associated with specific changes in the modulation of alpha and beta event-related synchronization/desynchronization. This unique study provides new perspectives for the assessment of functional deficits and changes in cortical activity promoted by rehabilitation in poststroke 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".