Alternating Current Stimulation for Essential Tremor
Bibliographic record
Abstract
Essential tremor is the most common movement disorder, characterized by involuntary rhythmic shaking of the hands, head, trunk, vocal cords, or legs. While the pathophysiological mechanisms of essential tremor are not fully understood, research suggests the involvement of a complex network called the cerebello-thalamo-cortical network. This network includes the inferior olive nuclei, cerebellum, red nucleus, thalamus, and cerebral cortex. Tremor generation in essential tremor is believed to be linked to neurodegeneration, abnormalities in a central oscillatory network, or dysfunction of the inhibitory neurotransmitter gamma-aminobutyric acid. Current treatments for essential tremor are largely unappealing to patients due to either being invasive (surgical), ineffective, and/or causing severe side effects. Previous studies on the impact of ACS in tremor are limited in number and lack a standardized protocol. The aim of this thesis was to investigate the effects of open-loop transcranial and transcutaneous alternating current stimulation on tremor in essential tremor, when delivered over the primary motor cortex and arm at a patient’s dominant tremor frequency. Our results revealed that both transcranial and transcutaneous open-loop alternating current stimulation, delivered to the primary motor cortex and upper arm at a patient’s dominant tremor frequency did not reduce tremor amplitude nor increase tremor ratio. Our study, being the first of its kind, informs on the need for more proof of principle studies in this field that will narrow down the most effective stimulation parameters, and structural targets.
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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 | 0.000 |
| 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) | 0.004 | 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".