The CovidSense project is funded by Khalifa University 8474000314 research grant. It is adapted within the Khalifa University research portfolio, to initiate a wide study network.
CovidSense aims to create a smartphone-based app that could provide a reliable Covid-19 risk index to the user before performing any relevant clinical test, monitor his/her symptoms, and provide guidance for further actions.
In this vein, CovidSense aims to provide a smartphone tool that could:
– collect metadata and self-reported health status data that relate with the aforementioned early Covid-19 symptoms,
– record physiological signals (such as breathing sounds, cough, heart rate) and GPS location,
– analyze the data via advanced machine/deep learning algorithms and devise a robust Covid-19 risk index, and
– provide reliable feedback to the user (via graphs, statistics, guidelines) and relevant stakeholders for handling and fighting Covid-19 spreading.
We would like to obtain data from the interaction of healthy controls as well as Covid-19 patients with their iPhones. This data, namely CoviData, comprises analyses of breathing and coughing sounds characteristics, location, heart rate. These data were identified based on existing coronavirus literature. You will be asked to provide electronic informed consent on the iPhone app in order to participate in this study.
CovidSense utilizes the ResearchKit SDK and follows the ResearchKit design guidelines provided by Apple to ensure a smooth experience while you register to the study as well as having the best experience while using the app.
Our app is deeply integrated with Health(TM) app in order to collect and display data collected by CovidSense and your iPhone. With our symptoms survey and daily tests, you can sync these data with your iOS devices and have a better understanding of your health.
Following this, our app will run on your smartphone and will notify you to provide data samples daily. This will allow CovideSense to collect daily data and study the risk of Covid-19.