NCT03169699

Acoustic Analytic Apps for Smart Telehealth Screening - Creating a Big Data

Status unknown Last updated 1 June 2017

What this trial tests

trial in URTI in 600 participants. Status unknown.

Timeline

1 February 2017

Primary endpoint
31 March 2018

31 March 2018

Quick facts

Lead sponsor	KK Women's and Children's Hospital
Status	Status unknown
Study type	OBSERVATIONAL
Enrollment	600
Start date	1 February 2017
Primary completion	31 March 2018
Estimated completion	31 March 2018
Sites	1 location across Singapore

Conditions studied

• URTI — all drugs for URTI →
• Cough — all drugs for Cough →
• Cough Variant Asthma — all drugs for Cough Variant Asthma →
• Cough; Bronchial, With Grippe or Influenza — all drugs for Cough; Bronchial, With Grippe or Influenza →

Sponsor

KK Women's and Children's Hospital

Who can join

Under 16, any sex, with URTI or Cough. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

To develop and validate a library of cough spectrum from a target of 1000 cough acoustics. Coughs arising from upper respiratory infection, lower chest infections, asthma, allergic conditions are included in the study. Cough acoustic in absence of respiratory disease is also included.

This is a prospective observation cohort study recruiting children below the age of 16 years old in 2 arms : (1) Patients with respiratory conditions presenting with cough and (2) Well patients without active coughing.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Deep Neural Network-Based Respiratory Pathology Classification Using Cough Sounds.
   Balamurali BT, Hee HI, Kapoor S, Teoh OH, et al · · 2021 · cited 13× · PMID 34450996 · DOI 10.3390/s21165555