Upload short recordings of cough and breathing and report symptoms to help researchers from the University of Cambridge detect if a person is suffering from COVID-19. Healthy and non-healthy participants welcome.
The app will collect some voice samples (while you read text on the screen), and a few seconds of breathing and coughing.
Contribute to science
We need many participants in order to build predictive models and contribute to the early diagnosis of COVID-19.
The app won't be tracking you and it will collect data when you actively interact with it.
The aims of this research
The aim of this research is to collect data to inform the diagnosis of COVID-19 by developing machine learning algorithms, based primarily on sounds of their voice, their breathing and coughing.
In order to enable this research we are launching a large scale, crowdsourced data collection from healthy and non-healthy participants through an application. The app will collect some basic demographics and medical history data, as well as some voice samples (while you read text on the screen) through a questionnaire and a few seconds of breathing and coughing through the phone microphone. We will additionally collect one location sample. The app will also ask if you have tested positive for the virus.
The app won't be tracking you and only collect this data when you actively interact with it. The data will be stored on University servers and be used solely for research purposes. We hope to release the dataset we are collecting to other researchers after the initial analysis and pre-processing. The app will not give medical advice and any reports of symptoms will not be responded to by medical assistance.
May 18, 2020 — Audio signals generated by the human body have often been used by clinicians and clinical researchers as diagnostic or progression...
The study has been approved by the Ethics Committee of the Department of Computer Science and Technology, University of Cambridge and is partly funded by the European Research Council through Project EAR.