Breathing Aid Devices to Support Novel Coronavirus (COVID-19)Infected Patients

被引:139
作者
Islam M.M. [1 ]
Ullah S.M.A. [2 ]
Mahmud S. [3 ]
Raju S.M.T.U. [1 ]
机构
[1] Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna
[2] Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology, Khulna
[3] Department of Computer Science, Kent State University, Kent, OH
关键词
Breathing aid; Continuous positive airway pressure; COVID-19; Novel coronavirus; Oxygen therapy device; Respiratory support; Ventilator;
D O I
10.1007/s42979-020-00300-1
中图分类号
学科分类号
摘要
Novel coronavirus (COVID-19), an ongoing pandemic, is threatening the whole population all over the world including the nations having high or low resource health infrastructure. The number of infection as well as death cases are increasing day by day, and outperforming all the records of previously found infectious diseases. This pandemic is imposing specific pressures on the medical system almost the whole globe. The respiration problem is the main complication that a COVID-19 infected patient faced generally. It is a matter of hope that the recent deployment of small-scale technologies like 3D printer, microcontroller, ventilator, Continuous Positive Airway Pressure (CPAP) are mostly used to resolve the problem associated with medical equipment’s for breathing. This paper aims to overview the existing technologies which are frequently used to support the infected patients for respiration. We described the most recent developed breathing aid devices such as oxygen therapy devices, ventilator, and CPAP throughout the review. A comparative analysis among the developed devices with necessary challenges and possible future directions are also outlined for the proper selection of affordable technologies. It is expected that this paper would be of great help to the experts who would like to contribute in this area. © 2020, Springer Nature Singapore Pte Ltd.
引用
收藏
相关论文
共 63 条
  • [1] Iyengar K., Mabrouk A., Jain V.K., Venkatesan A., Vaishya R., Learning opportunities from COVID-19 and future effects on health care system, Diabetes Metab Syndr Clin Res Rev, 14, pp. 943-946, (2020)
  • [2] Ayon S.I., Islam M.M., Hossain M.R., Coronary artery heart disease prediction: a comparative study of computational intelligence techniques, IETE J Res, (2020)
  • [3] Prediction of breast cancer using support vector machine and K-Nearest neighbors. In, IEEE Region 10 Humanitarian Technology Conference (R10-HTC), pp. 226-229, (2017)
  • [4] Hasan M.K., Islam M.M., Hashem M.M.A., Mathematical model development to detect breast cancer using multigene genetic programming, 5Th International Conference on Informatics, Electronics and Vision (ICIEV)., pp. 574-579, (2016)
  • [5] Haque M.R., Islam M.M., Iqbal H., Reza M.S., Hasan M.K., Performance Evaluation of Random Forests and Artificial Neural Networks for the Classification of Liver Disorder, International Conference on Computer, Communication, Chemical, Material and Electronic Engineering (IC4ME2, pp. 1-5, (2018)
  • [6] Islam Ayon S., Milon Islam M., Diabetes prediction: a deep learning approach, Int J Inf Eng Electron Bus, 11, pp. 21-27, (2019)
  • [7] A Combined Deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images, pp. 1-20, (2020)
  • [8] Muhammad L.J., Islam M.M., Usman S.S., Ayon S.I., Predictive data mining models for novel coronavirus (COVID-19) infected patients’ recovery, SN Comput Sci, 1, (2020)
  • [9] Wu Y.-C., Chen C.-S., Chan Y.-J., The outbreak of COVID-19, J Chin Med Assoc, 83, pp. 217-220, (2020)
  • [10] Namendys-Silva S.A., Respiratory support for patients with COVID-19 infection, Lancet Respir Med, 8, (2020)