Measurement of Osteoarthritic Patient Pain Through Electrodermal Activity Signals

NCT06701461 | Not Yet Recruiting FDA Device

• 1 other identifier: STUDY02002493
• Study Type: interventional
• Target: 15
• Locations: 1 country
• Sites: 1

Brief Summary

This pilot study aims to investigate the viability of using a smartwatch-based electrodermal activity (EDA) sensor to capture enough EDA signal to quantitatively assess pain in osteoarthritis subjects and test the feasibility of its methods and procedures for later use in subsequent larger-scale studies.

Conditions

Osteo Arthritis Knee

Keywords

Pain; Electrodermal Activity Signals; Osteoarthritis; Knee

Outcome Measures

Primary Outcomes (10)

• :Difference in pain measurements as reported by the participant via a visual analogue scale versus smartwatch reported electrodermal activity sensors

  As a pilot study, the goal is not hypothesis testing but rather examining the feasibility of this approach to measuring patient pain in osteoarthritic patients. Thus, the statistical analysis will be primarily descriptive. The baseline experiment is being done to see whether the smartwatch measurements are at all comparable to prior similar experiments using the thermal grill (Posada-Quintero 2016; Posada-Quintero 2021). For this reason, though not typical for a pilot study, participant responses to the baseline test will use similar analysis to prior electrodermal activity (EDA) based thermal grill studies to see if the smartwatch poses a viable EDA signal collection source. This primarily consists of repeated measures analysis of variance (ANOVA) comparing patient-reported visual analog scale (VAS) scores to EDA output.

  40 minutes of test time, occurring all in one day.

• Patient-reported pain during standardized Osteoarthritis Research Society International (OARSI) 30-second chair test

  Patients will be asked to participate in the standardized OARSI 30-second chair test. During the OARSI functional tests, the timestamps of patient reports of pain will be recorded by the experimenter.

  5 minutes

• Electrodermal activity (EDA) signals during standardized Osteoarthritis Research Society International (OARSI) 30-second chair test

  A smartwatch will capture the patient's EDA signals during the 30-second chair test

  0 minutes. Concurrent with measurement of patient-reported pain.

• Patient-reported pain during standardized Osteoarthritis Research Society International (OARSI) 40m fast-paced walk test

  Patients will be asked to participate in the standardized OARSI 40m fast-paced walk test. During the OARSI functional tests, the timestamps of patient reports of pain will be recorded by the experimenter.

  10 minutes

• Electrodermal activity (EDA) signals during standardized Osteoarthritis Research Society International (OARSI) 40m fast-paced walk test

  A smartwatch will capture the patient's EDA signals during the 40m fast-paced walk test

  0 minutes. Concurrent with measurement of patient-reported pain.

• Patient-reported pain during standardized Osteoarthritis Research Society International (OARSI) stair climb test

  Patients will be asked to participate in the standardized OARSI stair climb test. During the OARSI functional tests, the timestamps of patient reports of pain will be recorded by the experimenter.

  10 minutes

• Electrodermal activity (EDA) signals during standardized Osteoarthritis Research Society International (OARSI) stair climb test

  A smartwatch will capture the patient's EDA signals during the stair climb test

  0 minutes. Concurrent with measurement of patient-reported pain.

• Accuracy of predicting patient pain from electrodermal activity signal (EDA) during standardized Osteoarthritis Research Society International (OARSI) function tests

  We will treat the processed EDA signal as a binary classifier (i.e., prediction of pain or no pain at any given moment). The accuracy of these predictions will be calculated against the actual patient-reported pain.

  0 minutes. Done after all data has been collected.

• Percentage of correctly identified pain events (Sensitivity) as measured by the smartwatch (True positive events)

  In these tests, we will treat the processed EDA signal as a binary classifier (i.e., prediction of pain or no pain at any given moment). The sensitivity of these predictions will be calculated against the actual patient-reported pain.

  0 minutes. Done after all data has been collected.

• Percentage of correctly identified non-pain events (Specificity) as measured by the smartwatch (True negative non-events)

  In these tests, we will treat the processed EDA signal as a binary classifier (i.e., prediction of pain or no pain at any given moment). The specificity of these predictions will be calculated against the actual patient-reported pain.

  0 minutes. Done after all data has been collected.

Study Arms (1)

Electrodermal Activity Measurement Subjects

EXPERIMENTAL

Participants will have their baseline electrodermal activity (EDA) response to pain measured as well as their EDA response measured while participating in a set of standardized functional tests.

Device: Electrodermal Activity signal

Interventions

Electrodermal Activity signal DEVICE

Determining if the electrodermal activity signals, as measured by the Embrace Plus smartwatch) can be used to measure osteoarthritic patient pain levels.

Electrodermal Activity Measurement Subjects

Eligibility Criteria

• Age: 50 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Kellgren-Lawrence Grade \>= 3

You may not qualify if:

• Inflammatory arthropathy (e.g., rheumatoid arthritis), BMI \>=35
• Control subjects:
• Complaints of lower extremity joint pain
• Known diagnosis of knee osteoarthpathy
• Prior history of knee surgery, knee injections, or injury to knee joints (e.g., meniscus tears, ligamentous injuries), BMI \>=35
• Subjects with chronic heart problems, including, but not limited to, chronic hypertension, heart palpitations, a weak or irregular heartbeat, or a previous heart attack,
• Subjects taking the following drugs within 12 hours of the experiment or during the experiment: caffeine, alcohol, psychoactive drugs, nicotine or marijuana, other recreational drugs, and medicine of any kind that is not normally taken daily. Such medications include;
• NSAIDs
• Acetaminophen
• Steroidal anti-inflammatory agents
• Bronchodilators
• Appetite suppressants
• Lipase inhibitors
• Women who are currently pregnant
• Subjects with Raynaud's syndrome

Sponsors & Collaborators

• Dartmouth-Hitchcock Medical Center: lead
• University of Connecticut: collaborator

Study Sites (1)

Dartmouth-Hitchcock Medical Center

Lebanon, New Hampshire, 03756, United States

Location

Related Publications (2)

• Posada-Quintero HF, Florian JP, Orjuela-Canon AD, Chon KH. Highly sensitive index of sympathetic activity based on time-frequency spectral analysis of electrodermal activity. Am J Physiol Regul Integr Comp Physiol. 2016 Sep 1;311(3):R582-91. doi: 10.1152/ajpregu.00180.2016. Epub 2016 Jul 20.

  PMID: 27440716 BACKGROUND

• Posada-Quintero HF, Kong Y, Chon KH. Objective pain stimulation intensity and pain sensation assessment using machine learning classification and regression based on electrodermal activity. Am J Physiol Regul Integr Comp Physiol. 2021 Aug 1;321(2):R186-R196. doi: 10.1152/ajpregu.00094.2021. Epub 2021 Jun 16.

  PMID: 34133246 BACKGROUND

MeSH Terms

Conditions

Pain; Osteoarthritis

Condition Hierarchy (Ancestors)

Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Arthritis; Joint Diseases; Musculoskeletal Diseases; Rheumatic Diseases

Study Officials

• Peter L Schilling, MD, MS

  Dartmouth-Hitchcock Medical Center

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jon M Coordinator, MS

CONTACT

603-650-3306; jon.mikael.anderson@hitchcock.org

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor of Orthopaedics, Geisel School of Medicine, Dartmouth

Model Details: This preliminary study will look at the predictive effectiveness of the measured biomarker across a small group of patients with osteoarthritis and a small control group of patients without osteoarthritis.

Study Record Dates

• First Submitted: November 15, 2024
• First Posted: November 22, 2024
• Study Start (Estimated): August 1, 2026
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): October 1, 2026
• Last Updated: March 6, 2026

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)