A Review on Face Mask Detection Techniques for COVID-19 prevention

The World Health Organization (WHO) has stated two modes of transmission of the coronavirus disease (COVID-19) virus viz., respiratory droplets, and physical contact. Hence, there is a need to take some precautionary measures to avoid the spread of this virus such as social distancing and wearing masks. Between these two precautions, wearing a mask is considered to be the key factor for preventing the spread of the virus as these respiratory droplets can land on any surface. Therefore, keeping track of whether people are wearing masks or not is of utmost importance. Using deep learning, a computer-friendly COVID-19 face mask detector can be efficiently created that can help in identifying people without masks, thus, preventing COVID-19 from further spreading. This paper covers different techniques for detecting whether a person in the camera, picture, or video is wearing a mask or not. © 2022 IEEE.

Analysis of Respiratory Signals in Spectral Domain for Detecting Respiratory Disorders with Emphasis on COVID-19

Sound signals from different processes of respiratory system are vital indicators of human health. With the onset of Coronavirus pandemic, the importance of early diagnosis of respiratory disorders has further been highlighted. In this paper, research works related to analysis of respiratory system functioning in spectral domain using acoustic signal processing methods has been reviewed with special focus on work related to COVID-19 diagnosis using non-invasive techniques. Various deep learning and machine learning models for identifying acoustic biomarkers of COVID-19 have been studied and summarised. Three modalities that have been considered are breathing, cough and voice recordings. Feature extraction techniques on these modalities have been reviewed for classification, prediction and similarity metrics analysis. Another vital health parameter is the rate of respiration that can be estimated by performing spectral analysis of sound signal envelope of breathe signal recording. Various datasets and pre-processing techniques related to sounds associated with symptoms of respiratory disorders including COVID-19 sounds have also been listed. © 2022 IEEE.