Computer Aided Respiratory Therapy Based on Audio and Spirometry Signals

NCT ID: NCT06461195

Last Updated: 2024-06-14

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

15 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-06-25

Study Completion Date

2025-09-30

Brief Summary

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The purpose of the study is to collect data: audio in the form of respiratory sounds and instructions from the therapist, spirometry data during the execution of the therapy, physiological parameters, and patient information. With the help of this data, algorithms will be developed for the automatic detection, localization, and classification of respiratory sounds, linked to the respiratory cycle using spirometric signals.

Detailed Description

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The study is an interventional study. Patients receive their standard respiratory physiotherapy, but in the mean time they are monitored with a stethoscope, spirometer and a wearable to measure physio-logical parameters.

It has been chosen to intervene as little as possible in the therapy to measure the respiratory sounds and breathing of the patient as accurately as possible. By recording therapy sessions with 15 patients, we expect to register several hundred events of respiratory sounds. This provides a good foundation for training an algorithm to detect and classify respiratory sounds.

Conditions

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Respiratory Therapy

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Single group interventional study acquiring spirometry data, respiration sound and physiological data in patients suffering from pulmonary disease.
Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

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Regular respiratory physiotherapy while being monitored

Patients receive their standard respiratory physiotherapy, but in the mean time they are monitored with a stethoscope, spirometer and a wearable to measure physiological parameters.

Group Type EXPERIMENTAL

Monitoring of patients

Intervention Type OTHER

Data from a spirometer and a stethoscope are captured to develop algorithms to detect and classify respiration sounds to support therapists and patients in future therapy.

Interventions

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Monitoring of patients

Data from a spirometer and a stethoscope are captured to develop algorithms to detect and classify respiration sounds to support therapists and patients in future therapy.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* The patient has a chronic or acute respiratory condition and may need oxygen therapy
* The patient is minimally 12 years old

Exclusion Criteria

* The patient is cognitively impaired.
* The patient has an undrained pneumothorax.
* The patient is experiencing an acute pulmonary hemorrhage.
* The patient is having an asthma exacerbation.
* The patient has an infection with Burkholderia cepatia.
* The patient is in isolation due to the risk of infection.
Minimum Eligible Age

12 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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KU Leuven

OTHER

Sponsor Role collaborator

Universitair Ziekenhuis Brussel

OTHER

Sponsor Role collaborator

Lieven De Maesschalck

OTHER

Sponsor Role lead

Responsible Party

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Lieven De Maesschalck

Innovation Manager

Responsibility Role SPONSOR_INVESTIGATOR

Principal Investigators

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Filip Van Ginderdeuren, PhD

Role: PRINCIPAL_INVESTIGATOR

Universitair Ziekenhuis Brussel

Central Contacts

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Kris Cuppens, PhD

Role: CONTACT

+ 32 14 74 06 28

Filip Van Ginderdeuren, PhD

Role: CONTACT

Other Identifiers

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2023COMPASS-ST01

Identifier Type: -

Identifier Source: org_study_id

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