@inproceedings{lubeckeIdentificationCOVID19Type2021,
  title = {Identification of {{COVID-19 Type Respiratory Disorders Using Channel State Analysis}} of {{Wireless Communications Links}}},
  author = {Lubecke, Lana C. and Ishmael, Khaldoon and Zheng, Yao and Borić-Lubecke, Olga and Lubecke, Victor M.},
  date = {2021-10-31},
  abstract = {One deadly aspect of COVID-19 is that those infected can often be contagious before exhibiting overt symptoms. While methods such as temperature checks and sinus swabs have aided with early detection, the former does not always provide a reliable indicator of COVID-19, and the latter is invasive and requires significant human and material resources to administer. This paper presents a non-invasive COVID-19 early screening system implementable with commercial off-the-shelf wireless communications devices. The system leverages the Doppler radar principle to monitor respiratory-related chest motion and identifies breathing rates that indicate COVID-19 infection. A prototype was developed from software-defined radios (SDRs) designed for 5G NR wireless communications and system performance was evaluated using a robotic mover simulating human breathing, and using actual breathing, resulting in a consistent respiratory rate accuracy better than one breath per minute, exceeding that used in common medical practice.},
  eventtitle = {43rd {{Annual International Conference}} of the {{IEEE Engineering}} in {{Medicine}} and {{Biology Society}}},
  keywords = {conference}
}