The application of wearable smart sensors for monitoring the vital signs of patients in epidemics: a systematic literature review.
Niloofar MohammadzadehMarsa GholamzadehSoheila SaeediSorayya RezayiPublished in: Journal of ambient intelligence and humanized computing (2020)
Wearable smart sensors are emerging technology for daily monitoring of vital signs with the reducing discomfort and interference with normal human activities. The main objective of this study was to review the applied wearable smart sensors for disease control and vital signs monitoring in epidemics outbreaks. A comprehensive search was conducted in Web of Science, Scopus, IEEE Library, PubMed and Google Scholar databases to identify relevant studies published until June 2, 2020. Main extracted specifications for each paper are publication details, type of sensor, disease, type of monitored vital sign, function and usage. Of 277 articles, 11 studies were eligible for criteria. 36% of papers were published in 2020. Articles were published in 10 different journals and only in the Journal of Medical Systems more than one article was published. Most sensors were used to monitor body temperature, heart rate and blood pressure. Wearable devices (like a helmet, watch, or cuff) and body area network sensors were popular types which can be used monitoring vital signs for epidemic trending. 65% of total papers (n = 6) were conducted by the USA, Malaysia and India. Applying appropriate technological solutions could improve control and management of epidemic disease as well as the application of sensors for continuous monitoring of vital signs. However, further studies are needed to investigate the real effects of these sensors and their effectiveness.
Keyphrases
- heart rate
- low cost
- blood pressure
- heart rate variability
- end stage renal disease
- endothelial cells
- healthcare
- randomized controlled trial
- ejection fraction
- chronic kidney disease
- public health
- case control
- meta analyses
- physical activity
- machine learning
- systematic review
- artificial intelligence
- prognostic factors
- blood glucose
- patient reported outcomes
- big data