Wireless health monitoring with fuzzy decision tree for the community patients of chronic hypertension

Abstract

Health is an important factor needed by humans. There are many facilities for indicators of human health learning, including through the internet. Health monitoring that can be seen anywhere, in this case, a clinic or hospital with internet technology is one way to monitor the patient’s condition and is presented in the form of real-time data. One device that can be online is digital tensimeter, especially for patients in the hypertension community. Health indicator data such as systole, diastole, and heart rate values, are obtained easily so that they can be used to analyze the patient’s condition. The method as used is to use the hardware device ESP 8266 from an offline tensimeter device so that the data on the real condition of the patient can be read anywhere. In addition, this device saves the number of computer network nodes to connect to the internet. After the data is read, the data is processed using Fuzzy decision tree to analyze which patients need immediate care. The result is that from 150 measured data, the value of decision tree accuracy with Fuzzy process is obtained at 95%