| Autor: |
Shazwani Nor Razman, Nur Fatin, Nasir, Haslinah Mohd, Zainuddin, Suraya, Ariff Brahin, Noor Mohd, Ibrahim, Idnin Pasya, Mispan, Mohd Syafiq |
| Předmět: |
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| Zdroj: |
International Journal of Electrical & Computer Engineering (2088-8708); Dec2024, Vol. 14 Issue 6, p6929-6943, 15p |
| Abstrakt: |
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. Realtime 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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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