Predicting Acute Exacerbations of COPD Using Wearable Devices and Remote Monitoring Technology With AI/ML Models (ePredictAECOPD)

Early Prediction of Acute Exacerbations of COPD Using Wearable and Portable Remote Monitoring Technology With AI/ML Empowered Platforms: A Prospective Clinical Study

This study is aimed to collect real-time physiological data using two wearable devices (a biometric ring and a biometric wristband), daily lung mechanical measurements by a handheld oscillometer, and participant-reported symptoms in patients with COPD remotely from their home environment. The data will be used to train and validate artificial intelligence and machine learning (AI/ML) models to predict COPD exacerbations in advance of their actual occurrence. The data will also be used to test the new severity classification system for exacerbations of COPD, as well as to determine important relationships between physiological measurements from the wearable devices, the handheld oscillometer, the self-reported symptoms, and the tests performed at the baseline visit.

Study Overview

• Status: Recruiting
• Conditions: COPD; AE COPD
• Intervention / Treatment: Device: Biometric wearable and handheld devices

Detailed Description

A single-site, prospective, observational cohort study to collect high-quality multidimensional data from the wearable/portable devices, as well as symptom and exacerbation data, in high-risk patients with frequent exacerbations in order to develop a COPD exacerbation predictive model.

• Study Type: Observational
• Enrollment (Estimated): 50

Contacts and Locations

• Study Contact: Name: Bryan A. Ross, MD, MSc (Physiol), MSc (Epi); Phone Number: (514) 843-1465; Email: bryan.ross@mcgill.ca

Study Locations

• Canada
  • Quebec
    • Montreal, Quebec, Canada, H4A 3J1
      • Recruiting
      • McGill University Health Centre
      • Contact: Bryan A. Ross; Phone Number: (514) 843-1465; Email: bryan.ross@mcgill.ca

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with COPD with a documented history of frequent exacerbations.

While there is no specific method to estimate sample sizes for machine learning-based clinical research, based on two prior COPD studies measuring respiratory rate (RR) differences between stable-state and peak exacerbation phases, it was estimated that detecting a 4 breaths/min difference in RR (effect size 0.74) requires 17 prospectively collected exacerbation events, with alpha set to 0.05, power set to 0.8, and two-tailed analysis. Detecting a more subtle difference (i.e. 2 breaths/min; effect size 0.36) would require 63 events.

Assuming each participant experiences two exacerbations annually, 32 participants would meet these requirements. To account for the long observation period, the potential for non-events, and a 25% attrition rate, up to 50 participants will be recruited for this one-year study.

Description

Inclusion Criteria:

• Males/females, age ≥ 40, former/current smokers with ≥10 pack-year smoking history
• FEV1/FVC < 0.7, with 80% < FEV1 ≤50% (moderate, 'GOLD 2') 50% < FEV1 ≤ 30% (severe, 'GOLD 3') or FEV1 < 30% (very severe, 'GOLD 4') COPD
• History of 2 or more exacerbations in the preceding 12 months requiring corticosteroids, antibiotics, or both
• Ability to provide informed consent
• Ability to access internet at least once daily

Exclusion Criteria:

• No existing COPD diagnosis
• Any medical/cognitive/functional condition which renders inability to operate research equipment/devices, and/or to complete daily symptom response

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Respiration	Respiratory rate (RR) and respiratory rate variability (RRV) measured with wearable devices	Daily/nightly for 12 months
Cardiovascular	Heart rate (HR) and HR variability (HRV) measured with wearable devices	Daily/nightly for 12 months
Oxygen level	Blood oxygen saturation (SpO2) measured with wearable devices	Daily/nightly for 12 months
Step count	Parameter measured with wearable devices, related to activity.	Daily/nightly for 12 months
Sleep duration	Parameter measured with wearable devices.	Nightly for 12 months
Rapid eye movement (REM) sleep	Parameter measured with wearable devices.	Nightly for 12 months
Deep sleep	Parameter measured with wearable devices.	Nightly for 12 months
Body temperature	Peripheral body temperature measured with wearable devices	Nightly for 12 months
Resistance at 5 Hz (R5)	Parameter measured at 5 Hz frequency with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Reactance at 5 Hz (X5)	Parameter measured at 5 Hz frequency with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Intra-breath difference between expiratory and inspiratory reactance (ΔXrs)	Parameter measured with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Tidal volume (Vt)	Parameter measured with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Respiratory flows	Inspiratory and expiratory flows measured with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Respiratory rate (RR)	Parameter measured with handheld oscillometry.	Daily for 12 months
Minute ventilation (Ve)	Parameter measured with handheld oscillometry, related to lung mechanics/function.	Daily for 12 months
Heart rate (HR) prior oscillometry test	Parameter measured with handheld oscillometry before performing oscillometry test.	Daily for 12 months
Blood oxygen saturation (SpO2) prior oscillometry test	Parameter measured with handheld oscillometry before performing oscillometry test.	Daily for 12 months
Daily symptom questionnaire	• Visual analog scale (VAS) scores for dyspnea, sputum volume, sputum purulence, cough, wheeze, and fatigue, scaled 0-10. Higher scores indicate worse symptoms.	Daily for 12 months
Weekly exacerbation questionnaire	• Self report on any exacerbation(s) which occurred in the preceding week and their date(s), whether/how the exacerbation was treated, and in what treatment setting.	Weekly for 12 months
Calories	Parameter measured with wearable devices, related to activity.	Daily/nightly for 12 months
Metabolic equivalents	Parameter measured with wearable devices, related to activity.	Daily/nightly for 12 months
Movement intensity	Parameter measured with wearable devices, related to activity.	Daily/nightly for 12 months
Sleep efficiency	Parameter measured with wearable devices.	Nightly for 12 months
Sleep oncet	Parameter measured with wearable devices.	Nightly for 12 months
Sleep disturbance	Parameter measured with wearable devices.	Nightly for 12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
COPD Assessment Test (CAT)	Validated COPD questionnaire consisting of 8 questions and scaled 0-40. Higher scores indicate the severity of disease impact.	Once (baseline visit)
6-Minute Walk Test (6MWT)	Standard and validated assessment in COPD. Outcomes include distance walked as well as heart rate (HR), oxygen saturation (SpO2), and respiratory rate (RR) during the test. the 6MWT will be performed once at baseline while the participant is wearing the biometric wearable devices.	Once (baseline visit)
System Usability Scale (SUS)	Practical and reliable tool to determine the user experience with a variety of systems and devices. Scaled from 1-5, higher scores indicate better experience.	Through study completion, 1 year.

Collaborators and Investigators

• Sponsor: McGill University Health Centre/Research Institute of the McGill University Health Centre
• Collaborators: Restech Srl

Study record dates

Study Major Dates

• Study Start (Actual): May 22, 2025
• Primary Completion (Estimated): May 31, 2026
• Study Completion (Estimated): August 31, 2026

Study Registration Dates

• First Submitted: January 25, 2025
• First Submitted That Met QC Criteria: January 25, 2025
• First Posted (Actual): January 30, 2025

Study Record Updates

• Last Update Posted (Actual): May 28, 2025
• Last Update Submitted That Met QC Criteria: May 22, 2025
• Last Verified: May 1, 2025

More Information

Terms related to this study

• Keywords: chronic obstructive pulmonary disease (COPD); oscillometry; acute exacerbation of COPD (AECOPD); remote patient monitoring (RPM); artificial intelligence/machine learning (AI/ML); biometric wearable device
• Additional Relevant MeSH Terms: Pathologic Processes; Chronic Disease; Disease Attributes; Respiratory Tract Diseases; Lung Diseases; Lung Diseases, Obstructive; Pulmonary Disease, Chronic Obstructive
• Other Study ID Numbers: 2025-10606

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Due to data privacy regulations, individual participant data collected during this study is not publicly accessible. However, access to anonymized data may be granted upon evaluation by the trial management group. Additional documents will also be available upon inquiry. All requests should be directed to the corresponding author (BAR).

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No