Abstract
A multi-agent data-analytics-based approach to ubiquitous healthcare monitoring is presented in this paper. The proposed architecture gathers a patient’s vital data using wireless body area networks, and the transmitted information is separated into binary component parts and divided into related dataset categories using several classification techniques. A probabilistic procedure is then used that applies a normal (Gaussian) distribution to the analysis of new medical entries in order to assess the gravity of the anomalies detected. Finally, a data examination is carried out to gain insight. The results of the model and simulation show that the proposed architecture is highly efficient in applying smart technologies to a healthcare system, as an example of a research direction involving the Internet of Things, and offers a data platform that can be used for both medical decision making and the patient’s wellbeing and satisfaction with their medical treatment.
Highlights
Recent innovative works and research progress in the area of integrated circuits, wireless communications and sensors have allowed the creation of smart devices
We mainly chose the K-nearest neighbors (KNN) because of its non-parametric nature since it allowed the classifier to react promptly to input changes in real time, noting that it did not rely on data from a particular domain or a particular distribution
Since we were working on a binary class model, the point clouds might be linearly separable in the representation space, choosing a linear separator such as the linear discriminant analysis (LDA) seemed to be adequate to our purpose
Summary
Recent innovative works and research progress in the area of integrated circuits, wireless communications and sensors have allowed the creation of smart devices. Smart connected sensors are principal components of wireless body area networks (WBANs) and biosensors, and are fast becoming a key aspect of the Internet of Things. Technologies used in association with wireless sensor networks and the Internet of Things are closely linked to many fields, such as e-health [1], gaming, sports [2], military [3] and many applications are built in protected agriculture [4]. Ubiquitous systems offer the possibility of simplifying and easing access to health services [8], especially at the end of intensive care. Through collaboration between these smart systems, WBANs offer a number of medical sensors that are capable of gathering vital physiological information such as blood pressure, heart rate, oxygen saturation, etc. Through collaboration between these smart systems, WBANs offer a number of medical sensors that are capable of gathering vital physiological information such as blood pressure, heart rate, oxygen saturation, etc. and transmitting these data wirelessly to be analyzed for a given
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