Identification of Respiratory Profiles From Nasal Pressure Signals

NCT03753386 | Completed

• 1 other identifier: 2018-A01999-46
• Study Type: interventional
• Target: 20
• Locations: 1 country
• Sites: 1

Brief Summary

Chronic Obstructive Pulmonary Disease (COPD) is a chronic respiratory disease caused by smoking and associated with significant morbidity due to recurrent exacerbations or even hospitalizations. It is one of the leading causes of death in rich countries. Early detection of exacerbations of the disease is thus an economic and public health issue in the world. Finding tools for automatic and early detection of an exacerbation is the subject of the study. A continuous analysis of the frequency and shape of the patients' breathing will be used. As a first step in this study, investigators want to measure the frequency and shape of breathing in healthy subjects as they execute standard activities. These activities include resting, drinking, coughing, speaking, breathing through the mouth, physical exercise and recuperation.

Conditions

Healthy

Outcome Measures

Primary Outcomes (1)

• Pressure

  The monitoring device used records the nasal pressure from users at 10 Hz (one measure every 0.1 seconds).

  10 Hz for 30 minutes

Study Arms (1)

Healthy subjects

EXPERIMENTAL

Subjects not presenting any pulmonary pathology that will follow the intervention Oxygen therapy simulation.

Other: Oxygen therapy simulation

Interventions

Oxygen therapy simulation OTHER

The intervention consists of reproducing oxygen therapy situations in healthy individuals by replacing oxygen bottles with bottles of air. A TeleOx® device will be placed on the circuit between the source and the nasal cannula for respiratory signals recording. The intervention will last 30 minutes, containing the following activities in the given order: * rest (9 minutes); * drinking water (1 minute); * rest (1 minute); * coughing (1 minute); * rest (1 minute); * reading aloud (1 minute); * rest (1 minute); * breathing by the mouth (1 minute); * rest (1 minute); * exercising (running) (3 minutes) and * rest (10 minutes) Recordings will be retrieved after each test.

Healthy subjects

Eligibility Criteria

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

You may qualify if:

• Age of majority
• Health volunteers

You may not qualify if:

• Pregnancy
• Age of minority
• Protected adult
• Person deprived of liberty
• Respiratory pathology
• Non affiliation to the health care system

Sponsors & Collaborators

• Association pour le Développement et l'Organisation de la Recherche en Pneumologie et sur le Sommeil: lead
• SRETT: collaborator

Study Sites (1)

INSERM-UPC UMR_S 1158, Service de Pneumologie et Réanimation, GH Pitié-Salpêtrière

Paris, 75013, France

Location

Related Publications (1)

• Pegoraro JA, Lavault S, Wattiez N, Similowski T, Gonzalez-Bermejo J, Birmele E. Machine-learning based feature selection for a non-invasive breathing change detection. BioData Min. 2021 Jul 18;14(1):33. doi: 10.1186/s13040-021-00265-8.

  PMID: 34275469 DERIVED

Study Officials

• Jesus Gonzalez-Bermejo

  Groupe Hospitalier Pitié-Salpêtrière

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 21, 2018
• First Posted: November 27, 2018
• Study Start: May 16, 2019
• Primary Completion: May 16, 2019
• Study Completion: May 28, 2019
• Last Updated: September 16, 2019

Record last verified: 2019-09

Locations

FR (1)