Targeting motor and cognitive networks with multichannel transcranial direct current stimulation along with peripheral stimulation in a subacute stroke survivor: single case study
Bibliographic record
Abstract
Objective: Reacquisition of motor functions following stroke depends on interhemispheric neural connections.The intervention highlighted in the present case is an insight for augmenting motor recovery by stimulating the lesioned area and adjacent areas governing the motor behaviour of an individual.The purpose of this study was to determine the changes in the motor and cognitive outcomes through multi target stimulation of cortical areas by application of multichannel transcranial direct current stimulation (M-tDCS) in a stroke survivor.Design: A case report.Methods: The patient was a participant of a trial registered with the clinical trial registry of India (CTRI/2020/01/022998).The patient was intervened with M-tDCS over the left primary motor cortex i.e.C3 point and left dorsolateral prefrontal cortex i.e.F3 point with 0.5-2 mA intensity for the period of 20 minutes.SaeboFlex-assisted task-oriented training, functional electrical stimulation over the lower extremity (LE) to elicit dorsiflexion at the ankle and eversion of the foot, and conventional physiotherapy rehabilitation including a tailored exercise program were performed.Outcome assessment was done using the Fugl-Meyer assessment scale (FMA) for the upper and lower extremity (UE and LE), Montreal Cognitive Assessment (MOCA), Wisconsin Gait Scale (WGS) and the Stroke Specific Quality of Life (SSQOL) measures.Assessment was taken at Day 0, 15 and 30 post intervention.Results: Improvement was observed in all the outcome measures i.e FMA (UE and LE), MOCA, SSQOL and WGS across the span of 4 weeks.Conclusions: M-tDCS induced improvement in motor functions of the UE and LE, gait parameters and cognitive functions of the patient.
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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 | 0.002 | 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) | 0.003 | 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".