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Novel Coronavirus Cough Database: NoCoCoDa.

Madison Cohen-McFarlane1, Rafik Goubran1,2, Frank Knoefel1,2,3,4

  • 1Department of Systems and Computer EngineeringCarleton University Ottawa ON K1S 5B6 Canada.

IEEE Access : Practical Innovations, Open Solutions
|November 17, 2021
PubMed
Summary
This summary is machine-generated.

A new database of COVID-19 cough sounds (NoCoCoDa) was created from media interviews. This resource aids in developing audio-based tools for remote monitoring and analysis of coronavirus cough characteristics.

Keywords:
Acoustic signal processingaudio databasesaudio systemsbiomedical measurementbiomedical monitoringdata analysisdata collectionmedical conditionsmedical diagnosispatient monitoringsmart homes

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Area of Science:

  • Medical informatics
  • Respiratory medicine
  • Signal processing

Background:

  • The COVID-19 pandemic necessitates remote monitoring solutions for patient care and public health.
  • Audio-based sensing offers a non-intrusive method for analyzing cough characteristics.
  • Direct patient cough data collection is challenging during the pandemic.

Purpose of the Study:

  • To introduce the NoCoCoDa database as an interim solution for COVID-19 cough research.
  • To facilitate the development of algorithms for analyzing cough audio signals.
  • To support remote diagnosis, monitoring, and contact tracing of COVID-19.

Main Methods:

  • Collected COVID-19 cough events from public media interviews.
  • Manually segmented interviews to extract 73 individual cough events.
  • Annotated cough phases and classified cough subtypes (productive vs. dry).

Main Results:

  • The NoCoCoDa database contains 73 annotated COVID-19 cough events.
  • 77% of the coughs in the database were classified as productive.
  • Cough events were primarily recorded during or after severe disease periods.

Conclusions:

  • The NoCoCoDa database provides a valuable resource for rapid algorithm development in COVID-19 cough analysis.
  • This database can aid in creating real-time applications for remote patient monitoring.
  • NoCoCoDa is freely available to the research community.