Using Haptic Technology for Pain Reduction and Functional Improvement
Bibliographic record
Abstract
Advancements to reduce pain severity and improve functionality are generally lacking. Chronic or recurrent pain is the most common reason patients consult primary care clinicians. Adverse events associated with existing pharmacological pain treatments have incentivized researchers to identify effective pain treatment strategies that have limited side effects, including non-invasive and non-pharmacologic options. Research has shown that a clearer understanding of the pain neuromatrix may assist in identifying alternative approaches and improving patient outcomes. A network consisting of neuronal pathways and circuits responding to sensory (nociceptive) stimulation makes up the neuromatrix of pain. Research provides strong support that these pathways and areas of the brain have elicited change in response to external stimuli. Advancements in the understanding of how external tactile stimuli, specifically “haptic vibrotactile trigger technology (VTT)” disrupts the neuromatrix of pain, has led to the development of technology that shows promise in targeting the nociceptive pathways. Through ongoing research, the technology has been incorporated into non-invasive, non-pharmacological topical patches and other routes of delivery to evaluate response as it relates to different health concerns and conditions. The purpose of this IRB-approved, minimal risk, randomized, and blinded study was to evaluate patients’ experiences and/or perceptions and patient response for those who received a haptic vibrotactile trigger technology (VTT) embedded non-pharmacologic, non-invasive, over-the-counter pain patch (FREEDOM Super Patch with VTT; Srysty Holding CO, Toronto, Canada) and those who received a placebo patch without the embedded technology. This final outcome data from the HARMONI Study adds to previously published interim data. Methods: Baseline, 7- and 14-day data were recorded in one hundred sixty-eight (168) adult subjects (107 females and 61 males) in a Treatment Group (n=148) or Control Group (n=20) with a mean age of 53 years who presented with mild, moderate and even severe musculoskeletal, arthritic and neurological pain. The study evaluated changes in overall severity and interference scores via a validated scale (Brief Pain Inventory (BPI)), changes in the use of prescription and OTC medications, patient satisfaction, and any side effects reported while using an active or placebo patch. Results: For the Treatment Group, results showed statistically significant decreases in mean BPI severity and interference scores after using the VTT embedded pain patch. After 14 days, the vast majority of patients reported “less” or “a lot less” usage of oral medications and were very/extremely satisfied with the patch. Results also showed statistically significant and positive outcomes in all measured Quality of Life (QoL) components with improvements in general activity, mood, relations with other people, sleep, normal work, walking ability, and enjoyment of life. In the Control Group, there were no significant changes in pain severity, interference levels, usage of medications, and patient satisfaction was poor during the 14 day study period. Conclusions: Study results indicate that this non-pharmacologic, non-invasive, haptic vibrotactile trigger technology (VTT) embedded topical patch reduces pain severity and interference scores and may reduce the use of concurrent medications, including prescribed anti-inflammatory and other oral medication for adult patients with arthritic, neuropathic, and musculoskeletal pain. Results reported suggest that the non-pharmacological topical pain patch should be added to the current arsenal of noninvasive and nonpharmacological pain therapies.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".