International Journal of Electrical and Computer Engineering
Vol 14, No 6: December 2024

Systematic review: State-of-the-art in sensor-based abnormality respiration classification approaches

Razman, Nur Fatin Shazwani Nor (Unknown)
Nasir, Haslinah Mohd (Unknown)
Zainuddin, Suraya (Unknown)
Brahin, Noor Mohd Ariff (Unknown)
Ibrahim, Idnin Pasya (Unknown)
Mispan, Mohd Syafiq (Unknown)



Article Info

Publish Date
01 Dec 2024

Abstract

Respiration-related disease refers to a wide range of conditions, including influenza, pneumonia, asthma, sudden infant death syndrome (SIDS) and the latest outbreak, coronavirus disease 2019 (COVID-19), and many other respiration issues. However, real-time monitoring for the detection of respiratory disorders is currently lacking and needs to be improved. Real-time respiratory measures are necessary since unsupervised treatment of respiratory problems is the main contributor to the rising death rate. Thus, this paper reviewed the classification of the respiratory signal using two different approaches for real-time monitoring applications. This research explores machine learning and deep learning approaches to forecasting respiration conditions. Every consumption of these approaches has been discussed and reviewed. In addition, the current study is reviewed to identify critical directions for developing respiration real-time applications.

Copyrights © 2024






Journal Info

Abbrev

IJECE

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of ...