3D augmented reality mirror visual feedback therapy applied to the treatment of persistent, unilateral upper extremity neuropathic pain: a preliminary study
Why this work is in the frame
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Bibliographic record
Abstract
Objective: We assessed whether or not pain relief could be achieved with a new system that combines 3D augmented reality system (3DARS) and the principles of mirror visual feedback.Methods: Twenty-two patients between 18 and 75 years of age who suffered of chronic neuropathic pain. Each patient performed five 3DARS sessions treatment of 20 mins spread over a period of one week. The following pain parameters were assessed: (1) visual analogic scale after each treatment session (2) McGill pain scale and DN4 questionnaire were completed before the first session and 24 h after the last session.Results: The mean improvement of VAS per session was 29% (p < 0.001). There was an immediate session effect demonstrating a systematic improvement in pain between the beginning and the end of each session. We noted that this pain reduction was partially preserved until the next session. If we compare the pain level at baseline and 24 h after the last session, there was a significant decrease (p < 0.001) of pain of 37%. There was a significant decrease (p < 0.001) on the McGill Pain Questionnaire and DN4 questionnaire (p < 0.01).Conclusion: Our results indicate that 3DARS induced a significant pain decrease for patients who presented chronic neuropathic pain in a unilateral upper extremity. While further research is necessary before definitive conclusions can be drawn, clinicians could implement the approach as a preparatory adjunct for providing temporary pain relief aimed at enhancing chronic pain patients’ tolerance of manual therapy and exercise intervention.Level of Evidence: 4.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 it