Pain
Conditions
Keywords
Physiological markers for pain intensity, AI to objectively measure pain intensity, Medication over-use
Brief summary
The purpose of this research is to identify physiological markers to determine pain intensity and build an Artificial Intelligence (AI) enabled system to objectively measure pain intensity. Researchers hope to personalize pain medication regimens to help prevent medication over-use.
Interventions
OTHERMachine learning algorithms
Machine learning techniques to rank order physiologic variables obtained via the wearable and handheld devices as well as remove low-importance and redundant variables to accurately determine postoperative pain intensity in outpatients
Sponsors
Mayo Clinic
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Inclusion criteria
* Patients undergoing low-risk outpatient plastic surgery procedures with expected pain intensities ranging from mild to severe.
Exclusion criteria
* Patients with treated or untreated cardiopulmonary syndromes. * Patients with treated or untreated ophthalmologic pathologies. * Patients with skin pathologies that prevent us from using the TENS device. * Patients with pathologies or conditions preventing them from appropriately using their voice. * Patients with barriers to effective communication. * Patients with poor digital literacy. * Patients incapable of taking oral medication. * Patients who are currently taking medical therapy for chronic pain. * Patients with a previous diagnosis of severe anxiety disorders. * Patients who are immobile at baseline.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Using machine Learning for Postoperative Pain Pain Prediction | 8 months | The primary outcome will be the accuracy of machine learning algorithms for postoperative pain prediction using root mean square errors. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Physiologic variable %Δ defining the physiologic biomarker's change in measurements after pain medication | 8 months | The secondary outcome will be the physiologic variable's use to define the physiologic biomarker's change in measurements after pain medication (%Δ in signal's respective units). |
| Physiologic variable absolute Δ defining the physiologic biomarker's change in measurements after pain medication | 8 months | The secondary outcome will be the physiologic variable's use to define the physiologic biomarker's change in measurements after pain medication (absolute Δ in signal's respective units). |
Countries
United States
Outcome results
None listed