Diagnostic Risk Percentage Based on Vital Signs Readings on Health Monitoring Devices

Abstract

The development of the field of health technology has progressed rapidly - especially in the aspect of being connected to the Internet and also allowing the storage and monitoring of vital signs data utilizing IoT features. However, there is no health monitoring that contains advanced check-up analysis referring to the acquisition of vital signs data that has been stored in the health data record. This is exactly where additional parameters beyond the vital signs have not been integrated in health monitoring. The purpose of this independent research is to find a gap between industry and academia in the form of additional parameters that are not yet available in the industrial world. The additional parameter is the percentage value of health diagnostic risk. The selection of this parameter is based on the need to analyze the level of diagnostic risk through the acquisition of vital signs that have available readings in health monitoring device equipment. The algorithm mechanism itself revolves around mapping for the diagnosis of health conditions referring to the normal limits of vital signs utilizing the decision tree algorithm. The goal is none other than to simplify the flow in determining the patient's advanced health diagnosis. Regarding the diagnostic risk percentage parameter, the diagnosis and calculation include five vital signs that are the main indicators: heart rate, oxygen saturation (SPO2), body temperature (TBody) supplemented with skin temperature (TSkin), and respiratory rate.