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.
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.
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