Observational Study Using the CoVa Monitoring System 3

Baxter Healthcare Corporation14 enrolled

Overview

Asthma is a complex and chronic inflammatory disorder which is associated with reversible airway obstruction and bronchial hyperresponsiveness. It is one of the most prevalent chronic diseases in children and prevalence further increases worldwide. Typical symptoms of asthma are breathlessness, cough, wheezing and chest tightness. These symptoms are particularly prevalent at night-time. Understanding and tracking these symptoms can lead to better management of asthma. Auscultation using a stethoscope is standard clinical practice, however there is currently no available solution to detect respiratory sounds throughout the day and night. The aim of this study is to investigate the feasibility of detecting respiratory sounds in healthy children with the CoVa patch.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Healthy

Interventions

Cova Monitoring System 3DEVICE

Healthy Volunteers

Eligibility

Medical Language ↔ Plain English

Inclusion Criteria: * Participant is between the ages of 4 - 17 years old at the time of consent * Participant and/or family member/carer willing to give written consent * Participant and/or family member/carer who can read and comprehend english Exclusion Criteria: * Subject believed to be unsuitable for inclusion by the Principle Investigator * Subject is pregnant at time of consent * Subject is currently enrolled in another medical study

Outcomes

Primary Outcomes

Ability to detect simulated respiratory sounds including coughing and wheezing or identify subjects which have asthma related respiratory issues

Subjects will be asked to simulate coughing and wheezing sounds. This data will be analyzed by using a phonocardiogram (microphone) sensor.

Time frame: 2 Weeks

Secondary Outcomes

Ability to detect simulated respiratory sounds including wheeze and cough during movement such a simulated situation of moving in bed.

Subjects will be asked to simulate coughing and wheezing sounds. This data will be analyzed by using a phonocardiogram (microphone) sensor while the subject is moving in the bed.