Contactless Small-Scale Movement Monitoring System Using Software Defined Radio for Early Diagnosis of COVID-19.
Mubashir Rehman, Raza Ali Shah, Muhammad Bilal Khan, Najah Abed Abu Ali, Abdullah Alhumaidi Alotaibi, Turke Althobaiti, Naeem Ramzan, Syed Aziz Shah, Xiaodong Yang, Akram Alomainy, Muhammad Ali Imran, Qammer H Abbasi
Author Information
Mubashir Rehman: Department of Electrical EngineeringHITEC University Taxila 47080 Pakistan. ORCID
Raza Ali Shah: Department of Electrical EngineeringHITEC University Taxila 47080 Pakistan.
Muhammad Bilal Khan: School of Electronic EngineeringXidian University Xi'an 710071 China. ORCID
Najah Abed Abu Ali: Faculty of Information TechnologyUnited Arab Emirates University (UAEU) Al Ain United Arab Emirates. ORCID
Abdullah Alhumaidi Alotaibi: Department of Science and TechnologyCollege of RanyahTaif University Taif 21944 Saudi Arabia.
Turke Althobaiti: Faculty of ScienceNorthern Border University Arar 91431 Saudi Arabia.
Naeem Ramzan: School of Computing, Engineering and Physical SciencesUniversity of West Scotland (UWS) Glasgow G72 0LH U.K.
Syed Aziz Shah: Centre for Intelligent HealthcareCoventry University Coventry CV1 5FB U.K.
Xiaodong Yang: School of Electronic EngineeringXidian University Xi'an 710071 China. ORCID
Akram Alomainy: School of Electronic Engineering and Computer ScienceQueen Mary University of London London E1 4NS U.K. ORCID
Muhammad Ali Imran: School of EngineeringUniversity of Glasgow Glasgow G12 8QQ U.K. ORCID
Qammer H Abbasi: School of EngineeringUniversity of Glasgow Glasgow G12 8QQ U.K. ORCID
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.
