Infographic Visual Analytics based on Empirical Modelling for ICU patient data streams

The purpose of this research is to provide an environment for Infographic Visual Analytics model based on Empirical Modelling (IVAEM) for managing, analyzing and visualizing the ICU data streams of patient vital signs. The proposed method can help improve the human cognitive while interacting with the model. In particular, medical learners or practitioners can enhance their understanding of the patient symptom via the use of the proposed model in arbitrary ways to explore and observe the symptom of patient conveniently. The special kind of interaction of Empirical Modelling allows the users to learn, keep, and share their experience of the model. Empirical Modelling (EM) is a principle that can be used to build the interactive modelling on web-based environment to enable users to build artefacts in an unusually open-ended and flexible manner. In addition, user can freely create or define more formula and definition to the model on the domain of their study or observation. The Infographic Visual Analytics model proposed in this work is implemented using JS-Eden. JS-Eden is the web-based environment build under the principles of Empirical Modelling. This model allows users to visualize the data streams and analyze the vital signs' symptoms diagnosis. The diagnosis results come from the determination of dependencies between the thresholds and the actual value measured. JS-Eden provides the facility to visualize and analyze the multiple dimensions of ICU numeric data streams on an Infographic Visual Analytics platform. Multiple line charts and vital sign symptom annotated configurations offer a comprehensive tool to explore, analyze, observe, and learn about the critical level of patient symptom conveniently. Moreover, this type of model allows the reduction of cognitive burden in exploring multiple monitors and gaining insight or understanding of those physiological data behavior. Lastly, it can be further developed as a good monitoring technique to monitor multiple vital signs of patient in critical cases.