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False Alarm Reduction in ICU Using Ensemble Classifier Approach

V. Ravindra Krishna Chandar1,*, M. Thangamani2

1 Department of CSE, Paavai Engineering College, Namakkal, 637001, Tamilnadu, India
2 Department of Information Technology, Kongu Engineering College, Perundurai, 638052, Tamilnadu, India

* Corresponding Author: V. Ravindra Krishna Chandar. Email: email

Intelligent Automation & Soft Computing 2022, 34(1), 165-181. https://doi.org/10.32604/iasc.2022.022339

Abstract

During patient monitoring, false alert in the Intensive Care Unit (ICU) becomes a major problem. In the category of alarms, pseudo alarms are regarded as having no clinical or therapeutic significance, and thus they result in fatigue alarms. Artifacts are misrepresentations of tissue structures produced by imaging techniques. These Artifacts can invalidate the Arterial Blood Pressure (ABP) signal. Therefore, it is very important to develop algorithms that can detect artifacts. However, ABP has algorithmic shortcomings and limitations of design. This study is aimed at developing a real-time enhancement of independent component analysis (EICA) and time-domain detection of QRS that can be used to distinguish between imitation and false alarms. QRS detection is used to examine the waveform values appropriately by calculating the signal values, which are then utilized to identify the areas of high-frequency noise. AHE method is tapped to find the signal saturation values after the removal of such noise values. For artifact detection, Haar Wavelet Transform (HWT) and QRS detection methods are proposed. These operations are performed under the time domain. The classification model is proposed and trained by Fuzzy Neural Network (FNN), Extreme Random Trees (ERTs), and Extreme Learning Machine (ELM).


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APA Style
Chandar, V.R.K., Thangamani, M. (2022). False alarm reduction in ICU using ensemble classifier approach. Intelligent Automation & Soft Computing, 34(1), 165-181. https://doi.org/10.32604/iasc.2022.022339
Vancouver Style
Chandar VRK, Thangamani M. False alarm reduction in ICU using ensemble classifier approach. Intell Automat Soft Comput . 2022;34(1):165-181 https://doi.org/10.32604/iasc.2022.022339
IEEE Style
V.R.K. Chandar and M. Thangamani, "False Alarm Reduction in ICU Using Ensemble Classifier Approach," Intell. Automat. Soft Comput. , vol. 34, no. 1, pp. 165-181. 2022. https://doi.org/10.32604/iasc.2022.022339



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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