Combined transcranial direct current stimulation and robotic upper limb therapy improves upper limb function in an adult with cerebral palsy
Bibliographic record
Abstract
BACKGROUND: Robotic therapy can improve upper limb function in hemiparesis. Excitatory transcranial direct current stimulation (tDCS) can prime brain motor circuits before therapy. OBJECTIVE: We tested safety and efficacy of tDCS plus robotic therapy in an adult with unilateral spastic cerebral palsy (USCP). METHODS: In each of 36 sessions, anodal tDCS (2 mA, 20 min) was applied over the motor map of the affected hand. Immediately after tDCS, the participant completed robotic therapy, using the shoulder, elbow, and wrist (MIT Manus). The participant sat in a padded chair with affected arm abducted, forearm supported, and hand grasping the robot handle. The participant controlled the robot arm with his affected arm to move a cursor from the center of a circle to each of eight targets (960 movements). Motor function was tested before, after, and six months after therapy with the Wolf Motor Function Test (WMFT) and Fugl-Meyer (FM). RESULTS: Reaching accuracy on the robot task improved significantly after therapy. The WMFT and FM improved clinically meaningful amounts after therapy. The motor map of the affected hand expanded after therapy. Improvements were maintained six months after therapy. CONCLUSIONS: Combined tDCS and robotics safely improved upper limb function in an adult with USCP.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".