Literature DB >> 35789227

Contactless Small-Scale Movement Monitoring System Using Software Defined Radio for Early Diagnosis of COVID-19.

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


  7 in total

1.  Applications of software-defined radio (SDR) technology in hospital environments.

Authors:  Raúl Chávez-Santiago; Aleksandra Mateska; Konstantin Chomu; Liljana Gavrilovska; Ilangko Balasingham
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

2.  COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images.

Authors:  S Tabik; A Gomez-Rios; J L Martin-Rodriguez; I Sevillano-Garcia; M Rey-Area; D Charte; E Guirado; J L Suarez; J Luengo; M A Valero-Gonzalez; P Garcia-Villanova; E Olmedo-Sanchez; F Herrera
Journal:  IEEE J Biomed Health Inform       Date:  2020-12-04       Impact factor: 5.772

Review 3.  Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19.

Authors:  Feng Shi; Jun Wang; Jun Shi; Ziyan Wu; Qian Wang; Zhenyu Tang; Kelei He; Yinghuan Shi; Dinggang Shen
Journal:  IEEE Rev Biomed Eng       Date:  2021-01-22

4.  COVID-19 CT Image Synthesis with a Conditional Generative Adversarial Network.

Authors:  Yifan Jiang; Han Chen; M H Loew; Hanseok Ko
Journal:  IEEE J Biomed Health Inform       Date:  2020-12-04       Impact factor: 5.772

5.  Passive Radar for Opportunistic Monitoring in E-Health Applications.

Authors:  Wenda Li; Bo Tan; Robert Piechocki
Journal:  IEEE J Transl Eng Health Med       Date:  2018-01-25       Impact factor: 3.316

6.  COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks.

Authors:  Wenqi Shi; Li Tong; Yuanda Zhu; May D Wang
Journal:  IEEE J Biomed Health Inform       Date:  2021-07-27       Impact factor: 7.021

Review 7.  A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis.

Authors:  Christopher Clement John; VijayaKumar Ponnusamy; Sriharipriya Krishnan Chandrasekaran; Nandakumar R
Journal:  IEEE Rev Biomed Eng       Date:  2022-01-20
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.