sing Acoustic Tools to Improve Patient Experience with CPAP therapy

Not Applicable

Completed

• Conditions: Sleep Apnoea; Respiratory - Sleep apnoea

• Registration Number: ACTRN12618001649202
• Lead Sponsor: ResMed Ltd

Brief Summary

The Mask Identification Clinical Study was a single site pilot study for ongoing product development. Eighteen current PAP therapy users were provided with a new PAP therapy device with an external recording module to collect acoustic signals from their mask for a period of 7 nights. Participants used their device and current mask as normal, and completed a diary entry each night on their bedroom and PAP set-up. The study was conducted to evaluate the feasibility of using acoustic signals to accurately identify mask type in the user home environment. Participants in the study were those currently using CPAP therapy. Eighteen evaluable participants in total were targeted for this study. 6 participants of each of the following PAP mask types; ResMed P10, ResMed N20, ResMed F20. Acoustic signatures do not change significantly over multiple nights for a single patient, nor do they change significantly over time within a single night. However, although visual similarities are apparent, performance of a mask identification algorithm differ when training a machine learning model using controlled (bench) and field data. Training a model with controlled data alone is not representative of the home environment and leads to unsatisfactory classification of mask types from acoustic signatures acquired in the field.

Detailed Description

Not available

Study Timeline

• Results First Posted: 1900-01-01
• Study Start: 2018-10-05
• Study Completion: 2019-02-05
• Last Update Posted: 7 October 2019

Recruitment & Eligibility

• Status: Completed
• Sex: All
• Target Recruitment: 19

Inclusion Criteria

Patients willing to give written informed consent
Patients who can read and write English
Patients over 18 years of age
Patients established on CPAP therapy
Patients currently using an appropriate mask

Exclusion Criteria

Patients using bilevel devices
Patients who are using supplemental oxygen
Patients who are or may be pregnant
Patients with a preexisting lung disease/ condition that would predispose them to pneumothorax (for example: COPD, lung cancer; fibrosis of the lungs; recent (< 2years) case of pneumonia or lung infection; lung injury
Patients who are using another medical device concurrently
Patients believed unsuitable for inclusion by the researcher

Study & Design

• Study Type: Interventional
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
The primary objective is the cross-correlation of the acoustic signals recorded from the patient environment and the external recording in the controlled laboratory environment.[Nightly for 7 nights]

Secondary Outcome Measures

Name	Time	Method
Descriptive statistics on:<br><br>*Device location<br><br>Assessed via Audit of participant nightly diary<br>[Nightly for 7 nights]