Abstract
Contactless or non-invasive technology for the monitoring of anomalies in an inconspicuous and distant environment has immense significance in health-related applications, in particular COVID-19 symptoms detection, diagnosis, and monitoring. Contactless methods are crucial specifically during the COVID-19 epidemic as they require the least amount of involvement from infected individuals as well as healthcare personnel. According to recent medical research studies regarding coronavirus, individuals infected with novel COVID-19-Delta variant undergo elevated respiratory rates due to extensive infection in the lungs. This appalling situation demands constant real-time monitoring of respiratory patterns, which can help in avoiding any pernicious circumstances. In this paper, an Ultra-Wideband RADAR sensor enquote XeThru X4M200 is exploited to capture vital respiratory patterns. In the low and high frequency band, X4M200 operates within the 6.0-8.5 GHz and 7.25-10.20 GHz band, respectively. The experimentation is conducted on six distinct individuals to replicate a realistic scenario of irregular respiratory rates. The data is obtained in the form of spectrograms by carrying out normal (eupnea) and abnormal (tachypnea) respiratory. The collected spectrogram data is trained, validated, and tested using a cutting-edge deep learning technique called Residual Neural Network or ResNet. The trained ResNet model’s performance is assessed using the confusion matrix, precision, recall, F1-score, and classification accuracy. The unordinary skip connection process of the deep ResNet algorithm significantly reduces the underfitting and overfitting problem, resulting in a classification accuracy rate of up to 90%.
Highlights
C ORONAVIRUS is a broad family of viruses that can infect individuals and spread among humans in a varietyManuscript received August 26, 2021; revised August 28, 2021; accepted September 2, 2021
We present a system for monitoring COVID-19 patients that utilises off-the-shelf UltraWideband (UWB) RADAR sensor (XeThru X4M200 Respiration Sensor) created by NOVELDA [31]
To obtain distinct respiratory information, six human subjects were asked to sit on a chair in front of the UWB RADAR sensor at a distance of approximately 1 meter, XeThru X4M200 UWB RADAR sensor has the ability to capture vital signs up to 5 meters
Summary
C ORONAVIRUS is a broad family of viruses that can infect individuals and spread among humans in a variety. The respiratory rate and pulmonary function study of the identified patients, raises the danger of contagiousness due to the clinical urgency produced by COVID-19 [9]. Patients in self isolation whose pulmonary functions and respiratory rate are unaffected and do not require hospitalisation should be followed utilising telemedicine technology [12], [13]. We look at the prospect of adopting contactless (non-invasive/non-contact) technology to monitor real-time respiratory in COVID-19 patients. This type of RADAR sensor is capable to monitor several diseases’ symptoms through recognition of abnormal respiratory rates such as apnea, dyspnea, hyperpnea, tachypnea, hypopnea, bradypnea, orthopnea, platypnea, biot, cheyne-stokes, and kussmaul. The timely monitoring and detection of patients’ abnormal respiratory is of extreme significance, especially in the time of COVID-19
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