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Title:
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METHOD FOR ISOLATING THE PATIENT AND IoT
ABNORMALITY USING A BAYESIAN NETWORK |
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Author(s):
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Ryoichi Sasaki, Akinori Ueno and Jigang Liu |
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ISBN:
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978-989-8704-38-2 |
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Editors:
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Piet Kommers, Inmaculada Arnedillo Sánchez and Pedro Isaías |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Bayesian Network, Medical IoT, Patient Abnormality, Cause Isolation |
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First Page:
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53 |
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Last Page:
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60 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In recent years, Internet of Things (IoT) systems have become widespread. In the medical and health fields, the number
of systems that use IoT to detect and diagnose patient abnormalities is increasing. Even if an abnormality in a patient is
detected by such a system, it may actually be due to an abnormality in a component, such as the IoT. Therefore, when an
abnormality in a patient is detected, we have developed a method to determine whether the abnormality is a patient
abnormality or an abnormality in any part of the detection system using a Bayesian network. In addition, it was
confirmed that by applying this method to a patient abnormality detection system using an under-sheet-type multi-vital
IoT monitor in hospital, it is possible to isolate the cause of the abnormality appropriately and efficiently. |
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