AI-Based Wearable Sensing: A Technological Intervention to Physiological Monitoring and Early Detection of Pandemic Diseases

The COVID-19 pandemic has drastically left the world with a profound impact that will resonate for years to come. The devastating loss of lives, the dramatic decline in economic output, and the disruption of social interactions have all contributed to a sudden shift in our global landscape. Monitoring COVID-19 symptoms has become essential in controlling the spread of the virus and preventing hospitalizations. This paper presents an innovative solution that leverages advanced wearable technology integrated with cutting-edge artificial intelligence (AI) algorithms to monitor biometric signals associated with the presence of COVID-19 and other pandemic diseases. For persistent monitoring, the system is designed to acquire biometric signals such as temperature, heart rate, and blood oxygen saturation from wearable devices, which are considered as input to the long short-term memory (LSTM) network. The model will then reconstruct the signals, process them, and predict the health status of the patient with respect to the COVID-19 pandemic. Experiments were conducted to evaluate the performance of the system using two parameters i.e. temperature and heart rates. The system’s performance was compared to a certified medical station, and both heart rate and temperature parameter tests obtained good correlation (R=0. 73 and R=0. 96 respectively). This indicates the feasibility of the proposed system in early prediction of the presence of COVID-19, representing a crucial step forward in our efforts to build a more resilient and prepared world to navigate the challenges posed by the ever-present threat of future epidemics and pandemics.