Detection and Spatial Correlation Analysis of Infectious Diseases Using Wireless Body Area Network Under Imperfect Wireless Channel.
Big Data
; 10(1): 54-64, 2022 02.
Article
in English
| MEDLINE | ID: covidwho-1516499
ABSTRACT
The biosensors on a human body form a wireless body area network (WBAN) that can examine various physiological parameters, such as body temperature, electrooculography, electromyography, electroencephalography, and electrocardiography. Deep learning can use health information from the embedded sensors on the human body that can help monitoring diseases and medical disorders, including breathing issues and fever. In the context of communication, the links between the sensors are influenced by fading due to diffraction, reflection, shadowing by the body, clothes, body movement, and the surrounding environment. Hence, the channel between sensors and the central unit (CU), which collects data from sensors, is practically imperfect. Therefore, in this article, we propose a deep learning-based COVID-19 detection scheme using a WBAN setup in the presence of an imperfect channel between the sensors and the CU. Moreover, we also analyze the impact of correlation on WBAN by considering the imperfect channel. Our proposed algorithm shows promising results for real-time monitoring of COVID-19 patients.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Communicable Diseases
/
COVID-19
Limits:
Humans
Language:
English
Journal:
Big Data
Year:
2022
Document Type:
Article
Affiliation country:
BIG.2021.0187
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