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

Study Overview
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Brief Summary
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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.

Detailed Description
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Cough is a common presentation in childhood. It is one of the early symptom of respiratory disease such as upper respiratory tract infection, cough variant asthma, allergic rhinitis, bronchitis and pneumonia. These conditions are common ailments in childhood. The history of cough and description of cough given by caretakers and patients are often vague and assessment of cough quality is often subjective. The quality of cough is often assigned a dichotomous category of dry cough and wet cough. Computer assisted cough analysis has been developed in recent years to aid subjective classification of cough. The sound spectrum and frequencies of cough is being researched to better define the quality of cough. The quality of cough gives meaningful information about the state of the respiratory status. Cough sound analysis has been shown to rapidly diagnose pneumonia in humans using cough sound analysis and in differentiating wet and dry cough. The investigators hypothesize that each respiratory pathology will have its spectral cough characteristics. Analysis of cough spectrum and comparing to a library of cough spectra data will be able to aid differentiation of the underlying conditions for the various cough spectrum and hence facilitating management. The study aim is to develop a computer processing technique of cough sounds and determine their spectral characteristics for the common causes of cough to derive an assisted assay of cough spectrum for an objective assessment of cough.

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

Conditions
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URTI, Cough, Cough Variant Asthma, Cough; Bronchial, With Grippe or Influenza

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Cough arm 1.Children age 16 years old and below with cough at presentation- Patients presenting with active or chronic or residual cough Well arm 1.Children age 16 years old and below and Well with no cough presentation. Exclusion Criteria: Children with severe behavioral Droplet isloated cases as determined by protocol of hospital

Ages Eligible for Study
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Maximum Age: 16 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Cough Arm<br>Children age 16 years old and below with cough at presentation - Patients presenting with active or chronic or residual cough | |
| Well Arm<br>Children age 16 years old and below and Well with no presentation of cough | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Acute phase acoustic spectrum Analysis | Acoustic classifiers | Day 0-7 | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Recovery or Chronic phase acoustic spectrum analysis | Acoustic classifiers | Day 7-30 |