| Literature DB >> 35789227 |
Mubashir Rehman1, Raza Ali Shah1, Muhammad Bilal Khan2, Najah Abed Abu Ali3, Abdullah Alhumaidi Alotaibi4, Turke Althobaiti5, Naeem Ramzan6, Syed Aziz Shah7, Xiaodong Yang2, Akram Alomainy8, Muhammad Ali Imran9,10, Qammer H Abbasi9.
Abstract
The exponential growth of the novel coronavirus disease (N-COVID-19) has affected millions of people already and it is obvious that this crisis is global. This situation has enforced scientific researchers to gather their efforts to contain the virus. In this pandemic situation, health monitoring and human movements are getting significant consideration in the field of healthcare and as a result, it has emerged as a key area of interest in recent times. This requires a contactless sensing platform for detection of COVID-19 symptoms along with containment of virus spread by limiting and monitoring human movements. In this paper, a platform is proposed for the detection of COVID-19 symptoms like irregular breathing and coughing in addition to monitoring human movements using Software Defined Radio (SDR) technology. This platform uses Channel Frequency Response (CFR) to record the minute changes in Orthogonal Frequency Division Multiplexing (OFDM) subcarriers due to any human motion over the wireless channel. In this initial research, the capabilities of the platform are analyzed by detecting hand movement, coughing, and breathing. This platform faithfully captures normal, slow, and fast breathing at a rate of 20, 10, and 28 breaths per minute respectively using different methods such as zero-cross detection, peak detection, and Fourier transformation. The results show that all three methods successfully record breathing rate. The proposed platform is portable, flexible, and has multifunctional capabilities. This platform can be exploited for other human body movements and health abnormalities by further classification using artificial intelligence.Entities:
Keywords: CFR; COVID-19; OFDM; SDR; USRP; breathing rate measurement
Year: 2021 PMID: 35789227 PMCID: PMC8791440 DOI: 10.1109/JSEN.2021.3077530
Source DB: PubMed Journal: IEEE Sens J ISSN: 1530-437X Impact factor: 4.325