Lung sound characterization

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Objectives	Overall Objectives: To collect audio recording of various lung sounds and heart sounds from children and adults to create a database and computer algorithm to recognize various respiratory disease conditions using machine learning and artificial intelligence algorithms. Specific objectives Phase I: Current protocol To collect audio recordings of lung and heart sounds from children with respiratory illnesses including pneumonia, bronchiolitis, cystic fibrosis (CF), reactive airway disease (including asthma), upper respiratory illness (URI) and also normal sounds (classified by a clinician specialist/pediatrician) that will be used for developing the algorithm. To collect audio recordings of lung and heart sounds from adults with respiratory illnesses including pneumonia, asthma, chronic obstructive pulmonary diseases (COPD), as well as normal sounds (classified by a specialist- Medicine/Pulmonary Medicine) that will be used for developing the algorithm. To develop a computer algorithm to calculate respiratory rate and heart rate and to recognize the respiratory diseases (upper respiratory infection, cystic fibrosis, pneumonia, asthma, chronic bronchitis) based on the qualitative features of the breath sounds in children and adults using techniques borrowed from Computer Science such as Machine Learning, Data Mining and Artificial Intelligence.
Timeline	Apr 2019 to Aug 2019
Location
Methods
Expected Outcomes

Principal Investigator

Dr. Manoja K.Das

Co-PI’s

Implementation Team

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