Virtual Reality in Fibromyalgia: Does Altering Visual Feedback Impact on Pain and Movement During Reaching?
Bibliographic record
Abstract
People with fibromyalgia (FM) have movement-related fear impacting on daily activities. While virtual reality has been used as a distractor to promote exercise, it can be used to manipulate visual feedback (VF) about movement, potentially influencing pain and movement. Objectives: A. To determine whether altered VF modulates pain during movement; B. To compare adaptation to an altered VF between FM participants and healthy controls (HC); C. To explore relationships between adaptation, limb position sense, kinesiophobia and pain. 20 FM participants and 20 HC performed a reaching task during two sessions in a KINARM exoskeleton including a virtual reality interface allowing to replace their arm with a virtual arm. In one session, VF was altered to show GREATER movements while in the other it showed SMALLER movements (randomized order). Pain was assessed periodically using a numerical rating scale. Movement amplitude was assessed during exposure to altered VF (adaptation) and pre-/post-exposure (without VF; after-effects). Limb position sense was assessed with a KINARM task, and kinesiophobia was assessed with the Tampa Scale for Kinesiophobia (TSK-11). Pain intensity increased slightly with movement repetitions (p < 0.001), but did not differ between the VF conditions (GREATER vs. SMALLER). Both groups exhibited visuomotor adaptation, as shown by VF-dependent changes in movement amplitude and speed during exposure to altered VF, and by the presence of VF-dependent after-effects (p < 0.001 for all variables). However, no differences were observed across groups for any of these variables, despite the fact that FM had significantly more difficulty to correctly detect VF conditions than HC (p = 0.046). No clear limb position sense deficits were observed in FM participants, and no significant relationships were found between TSK-11 scores and changes in pain intensity during exposure to altered VF. Altering VF did not influence pain during a reaching task in the FM group. Surprisingly, both groups adapted similarly to altered VF. Visuomotor adaptation is therefore preserved in FM, despite impairments in sensory perception and the poor ability to detect VF alterations in the present study. Further research is warranted to clarify the relationship between sensory perceptions and motor control in FM.
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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 | 0.002 |
| 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".