Assessment of rehabilitation of corpus callosum infarction: a case report based on functional near infrared spec-troscopy
Bibliographic record
Abstract
Objective To report the individualized rehabilitation protocol administered to a patient suffering from corpus callosum injury subsequent to cerebral infarction, manifesting clinically as alien hand syndrome, attention deficits, spatial neglect and gait apraxia; and to emphasize the application of functional near infrared spectroscopy (fNIRS) in the assessment of cerebral activation. Methods A 54-year-old male with corpus callosum damage following cerebral infarction was assessed by a comprehensive array of neuropsychological assessments, such as Mini-Mental State Examination, Montreal Cognitive Assessment, Loewenstein Occupational Therapy Cognitive Assessment and Wisconsin Card Sorting Test, etc. Based on these assessments, a personalized rehabilitation program was devised, incorporating physical therapy, occupational therapy, task-oriented training, mirror therapy, computer-assisted cognitive training, as well as Schulte's square attention training, bilateral limb coordination training and transcranial magnetic stimulation (TMS).fNIRS was used to evaluate changes in brain activation before and after rehabilitation. Results After more than a month of comprehensive rehabilitation, the patient experienced significant improvements in Alien hand syndrome, attention deficit and spatial neglect. Gait was normalized, and enhancements were observed in motor function, cognition and activity of daily living. fNIRS analysis revealed favorable alterations in cerebral activation patterns. Conclusion For the intricate symptoms associated with corpus callosum injury, a multidisciplinary rehabilitation approach, particularly the incorporation of Schulte's square attention training, bilateral coordination exercises and TMS, alongside fNIRS for monitoring cerebral activation, showed significant rehabilitation effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".