Smarty4Covid Dataset

Overview

The idea of harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and the progress of respiratory abnormalities/conditions, has motivated several research endeavours in applying signal analysis and AI on audio recordings of cough, voice and breath with the ultimate goal to detect innovative COVID-19 related bio-markers. The Smarty4Covid dataset contains audio signals of cough, deep breathing and regular breathing as recorded by means of different devices through following a crowd-sourcing approach supported by a responsive web-based application. In addition, it includes self-reported information, such as demographics, symptoms and results of COVID-19 tests.

Data structure

The main directory is organized as shown in the figure below. It contains sub-directories, each including the submissions of  a specific participant. Each submission includes: (i) a unique json file (“patient.v3.json”) containing information about demographics (e.g. BMI, age, sex, presence of potential underlying medical conditions), (ii) audio recordings of cough (“cough.mp3”) and deep breathing (“breath_2.mp3”) and (iii) a json file "questionnaire..v3.json" containing the self reported information related to the COVID-19 test (result, type and date of the test), vaccination against COVID-19 status, COVID-19 related symptoms, vital signs and more. The multiple submissions of a particular participant are distinguished by applying unique questionnaire ids.

A detailed description of the various JSON files and their fields is provided in README.pdf file.

├── ...
│
├──
│   ├── patient.v3.json
│   ├── questionnaire..audio.breath_2.mp3
│   ├── questionnaire..audio.cough.mp3
│   ├── questionnaire..v3.json
│   ├── ...
│   ├── questionnaire..audio.breath_2.mp3
│   ├── questionnaire..audio.cough.mp3
│   └── questionnaire..v3.json
├── ...
│
└── README.pdf