2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 13 , Issue 1 , PP: 59-70, 2024 | Cite this article as | XML | Html | PDF
Zainab A. Wajeeh 1 * , Sadiq J. Hamandi 2 , Wisam S. Alobaidi 3
Doi: https://doi.org/10.54216/JISIoT.130105
Cardiovascular diseases detection or diagnosis on appropriate time is crucial to avoid health complications. In this study, an advanced procedure for classifying changes in the blood pressure has been used analyzing the wave-forms inside the arterial system where such variation can occur due to improper timing in intra-aortic balloon pump (IABP) control. Inaccurate pressure extends with probable injury can be caused by improper timing in the heart valve in both pumping and compression of the balloon. This investigation focuses on accurately recognizing and classifying any irregularities in the artery wave-forms in IABP in the blood pressure initiated by mistiming. Accumulated blood pressure records are used for the progression of providing information to IABP trainer. The wave-forms require pre-handling employing image digitizing software to acquire automated identifications. Any undesirable image features have been removed using Wavelet in MATLAB software. Afterward, such features can be employed to develop a technique for arrangement depending on neural networks. The artificial neural network technique has used marked data to properly detect irregularities in wave-forms in vascular blood pressure due to improper IABP timing. As a result, the validation has proved to appropriately recognize and classify such anomalies, denoting a considerable prospect to improve patient protection with an efficacy of treatment in the area of cardiovascular prescription.
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Intra-aortic balloon pump , arterial blood pressure wave , IABP trainer , machine learning timing , neural network , arrangement algorithm
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