Mirror Visual Feedback Combining Vibrotactile Stimulation Promotes Embodiment Perception: An Electroencephalogram (EEG) Pilot Study
Bibliographic record
Abstract
As one determinant of the efficacy of mirror visual feedback (MVF) in neurorehabilitation, the embodiment perception needs to be sustainable and enhanced. This study explored integrating vibrotactile stimulation into MVF to promote the embodiment perception and provide evidence of the potential mechanism of MVF. In the experiment, the participants were instructed to keep their dominant hand still (static side), while open and close their non-dominant hand (active side) and concentrate on the image of the hand movement in the mirror. They were asked to tap the pedal with the foot of the active side once the embodiment perception is generated. A vibrotactile stimulator was attached on the hand of the active side, and three conditions were investigated: no vibration (NV), continuous vibration (CV), and intermittent vibration (IV). The effects were analyzed on both objective data, including latency time (LT) and electroencephalogram (EEG) signals, and subjective data, including embodiment questionnaire (EQ). Results of LT and EQ suggested a stronger subjective sense of embodiment under the condition of CV and IV, comparing with NV. No significant difference was found between CV and IV. EEG analysis showed that in the hemisphere of the static side, the desynchronization of CV and IV around the central-frontal region (C3 and F3) in the alpha band (8-13 Hz) was significantly prominent compared to NV, and in the hemisphere of the active side, the desynchronization of three conditions was similar. The network analysis of EEG data indicated that there was no significant difference in the efficiency of neural communication under the three conditions. These results demonstrated that MVF combined with vibrotactile stimulation could strengthen the embodiment perception with increases in motor cortical activation, which indicated an evidence-based protocol of MVF to facilitate the recovery of patients with stroke.
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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) | 0.002 | 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".