Wearable Technology to Assist the Patients Infected with Novel Coronavirus (COVID-19)

被引：42

作者：

Islam M.M. ^{[1
]}

Mahmud S. ^{[2
]}

Muhammad L.J. ^{[3
]}

Islam M.R. ^{[4
]}

Nooruddin S. ^{[1
]}

Ayon S.I. ^{[5
]}

机构：

[1] Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna

[2] Department of Computer Science, Kent State University, Kent, OH

[3] Department of Mathematics and Computer Science, Faculty of Science, Federal University of Kashere, P.M.B. 0182, Gombe

[4] Department of Electrical and Electronic Engineering, Bangladesh Army University of Engineering and Technology, Natore

[5] Department of Computer Science and Engineering, Green University of Bangladesh, Dhaka

来源：

SN Computer Science | 2020年 / 1卷 / 6期

关键词：

COVID-19; Novel coronavirus; Respiratory support; Symptoms monitoring; Wearable technology;

D O I：

10.1007/s42979-020-00335-4

中图分类号：

学科分类号：

摘要：

Wearable technology plays a significant role in our daily life as well as in the healthcare industry. The recent coronavirus pandemic has taken the world’s healthcare systems by surprise. Although trials of possible vaccines are underway, it would take a long time before the vaccines are permitted for public use. Most of the government efforts are currently geared towards preventing the spread of the coronavirus and predicting probable hot zones. The essential and healthcare workers are the most vulnerable towards coronavirus infections due to their required proximity to potential coronavirus patients. Wearable technology can potentially assist in these regards by providing real-time remote monitoring, symptoms prediction, contact tracing, etc. The goal of this paper is to discuss the different existing wearable monitoring devices (respiration rate, heart rate, temperature, and oxygen saturation) and respiratory support systems (ventilators, CPAP devices, and oxygen therapy) which are frequently used to assist the coronavirus affected people. The devices are described based on the services they provide, their working procedures as well as comparative analysis of their merits and demerits with cost. A comparative discussion with probable future trends is also drawn to select the best technology for COVID-19 infected patients. It is envisaged that wearable technology is only capable of providing initial treatment that can reduce the spread of this pandemic. © 2020, Springer Nature Singapore Pte Ltd.

引用

共 64 条

[1]

Guan W., Ni Z., Hu Y., Liang W., Ou C., He J., Liu L., Shan H., Lei C., Hui D.S.C., Du B., Li L., Zeng G., Yuen K.-Y., Chen R., Tang C., Wang T., Chen P., Xiang J., Li S., Wang J., Liang Z., Peng Y., Wei L., Liu Y., Hu Y., Peng P., Wang J., Liu J., Chen Z., Li G., Zheng Z., Qiu S., Luo J., Ye C., Zhu S., Zhong N., Clinical characteristics of coronavirus disease 2019 in China, N Engl J Med, 382, pp. 1708-1720, (2020)

[2]

Ksiazek T.G., Erdman D., Goldsmith C.S., Zaki S.R., Peret T., Emery S., Tong S., Urbani C., Comer J.A., Lim W., Rollin P.E., Dowell S.F., Ling A.-E., Humphrey C.D., Shieh W.-J., Guarner J., Paddock C.D., Rota P., Fields B., DeRisi J., Yang J.-Y., Cox N., Hughes J.M., LeDuc J.W., Bellini W.J., Anderson L.J., A novel coronavirus associated with severe acute respiratory syndrome, N Engl J Med, 348, pp. 1953-1966, (2003)

[3]

Rabi F.A., Al Zoubi M.S., Kasasbeh G.A., Salameh D.M., Al-Nasser A.D., SARS-CoV-2 and coronavirus disease 2019: what we know so far, Pathogens, 9, (2020)

[4]

Peiris J., Lai S., Poon L., Guan Y., Yam L., Lim W., Nicholls J., Yee W., Yan W., Cheung M., Cheng V., Chan K., Tsang D., Yung R., Ng T., Yuen K., Coronavirus as a possible cause of severe acute respiratory syndrome, Lancet, 361, pp. 1319-1325, (2003)

[5]

Tang B., Bragazzi N.L., Li Q., Tang S., Xiao Y., Wu J., An updated estimation of the risk of transmission of the novel coronavirus (2019-nCov), Infect Dis Model, 5, pp. 248-255, (2020)

[6]

Liu T., Hu J., Xiao J., He G., Kang M., Rong Z., Lin L., Zhong H., Huang Q., Deng A., Zeng W., Tan X., Zeng S., Zhu Z., Li J., Gong D., Wan D., Chen S., Guo L., Li Y., Sun L., Liang W., Song T., He J., Ma W., Time-varying transmission dynamics of novel coronavirus pneumonia in China, BioRxiv, (2020)

[7]

Yue T., Fan Z., Fan B., Du Z., Wilson J.P., Yin X., Zhao N., Wang Y., Zhou C., A new approach to modeling the fade-out threshold of coronavirus disease, Sci Bull, 65, pp. 1225-1227, (2020)

[8]

Ayon S.I., Islam M.M., Hossain M.R., Coronary artery heart disease prediction: a comparative study of computational intelligence techniques, IETE J Res, pp. 1-20, (2020)

[9]

Islam Ayon S., Milon Islam M., Diabetes prediction: a deep learning approach, Int J Inf Eng Electron Bus, 11, pp. 21-27, (2019)

[10]

Islam M.M., Haque M.R., Iqbal H., Hasan M.M., Hasan M., Kabir M.N., Breast cancer prediction: a comparative study using machine learning techniques, SN Comput Sci, 1, (2020)

← 1 2 3 4 5 6 7 →