Reducing Sleep Disorder and Insomnia Related Symptoms with Haptic Technology
Bibliographic record
Abstract
There are several diseases that are associated with sleep disorders and many current pharmacological approaches have been shown to have significant side effects. Sleep issues are widely prevalent in the US, with an estimate of 50-70 million people having chronic, or ongoing, sleep disorders. The importance of sleep health significantly impacts overall physical health, behavioral health, wellness, and safety and should not be underestimated or ignored. Identifying alternative treatments, including non-invasive and non-pharmacologic options and that are safe, efficacious, and have reduced and limited side effect profiles, will provide options that may be preferred over conventional therapies and how clinicians treat sleep disorders. Ongoing research focusing on different brain centers has shown that areas of the brain can respond to external stimuli. Haptic vibrotactile trigger technology (VTT) is designed and theorized to target the pathways and influence these brain centers. The technology has been incorporated into non-invasive, non-pharmacological topical patches and other routes of delivery. The purpose of this IRB-approved, blinded, minimal-risk observational 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 sleep patch (REM Sleep Patch with VTT; Super Patch Company, Srysty Holding Co, Toronto, Canada) with those who received a control patch without the embedded VTT technology. Methods: Baseline, 7- and 14-day data were recorded in one hundred thirteen (133) adult subjects (87 females and 46 males) with a mean age of 53 years (Treatment Group) and 60 years (Control Group) who presented with sleep- or insomnia- related issues or associated symptoms. The study evaluated changes in overall sleep quality and insomnia severity scores via validated scales including the PSQI (Pittsburgh Sleep Quality Index) and the ISI (Insomnia Severity Index), changes in nighttime awakenings, the use of prescription and OTC medications, patient satisfaction, and any side effects reported while using the patches. Results: After using the VTT embedded sleep patch, results showed statistically significant decreases in time to fall asleep, an increase in number of hours of sleep, improvement in the quality of sleep, and reduction in global PSQI Score. After 14 days, the vast majority of patients in the Treatment Group reported a reduction of usage of oral medications, that the patch was convenient and easy to use, and preferred the patch over oral and other medications for sleep. Results also showed positive outcomes in Quality of Life (QoL) components with improvements in daytime fatigue, mood, ability to function at work/daily chores, concentration, memory, and mood. After 14 days for those subjects assigned to the Control Group using a patch not embedded with VTT technology, there were no improvements in time to fall asleep, number of hours of sleep, improvement in the quality of sleep, change in use of oral medications, change in daytime fatigue, mood, ability to function at work/daily chores, concentration, memory, and mood. Conclusions: Study results indicate that this non-pharmacologic, non-invasive, haptic vibrotactile trigger technology (VTT) embedded topical patch improves sleep quality, duration, and quality-of-life components and may reduce the use of concurrent medications, including prescribed and other oral medication for adult patients with sleep or insomnia-related symptoms compared to those subjects using a patch not embedded with VTT. Results reported support the use of this non-pharmacological, VTT-embedded, topical sleep patch to the current approaches and treatments of noninvasive and nonpharmacological sleep therapies.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".