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OpenTrials
Enrolling by Invitation

NCT Number: NCT05474274

PAIN (Pain AI iNtervention) Platform for Patients at Home

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.

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Key information

Conditions

Pain Neurologic Manifestations Pathological Conditions, Signs and Symptoms Signs and Symptoms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Mayo Clinic Florida

Jacksonville, Florida, 32224, United States

Who can participate

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Machine learning algorithms

Other

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

Other names: Artificial Intelligence (AI) enabled system

Primary outcomes

  1. Using machine Learning for Postoperative Pain Pain Prediction

    Time frame: 8 months

    The primary outcome will be the accuracy of machine learning algorithms for postoperative pain prediction using root mean square errors.

Secondary outcomes

  1. Physiologic variable %Δ defining the physiologic biomarker's change in measurements after pain medication

    Time frame: 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).

  2. Physiologic variable absolute Δ defining the physiologic biomarker's change in measurements after pain medication

    Time frame: 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).

Sponsors and collaborators

Lead sponsor

Mayo Clinic

Other

Registry information

Official study title

Development of the PAIN (Pain AI iNtervention) Platform for Patients at Home

Important dates

Study start
2022
Primary completion
2026
Study completion
2027
First posted
Jul 26, 2022
Registry last updated
Dec 22, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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