Smart Healthcare System Using Back-Propagation Algorithm

Abstract

The recent increase in social needs due to the development and aging of devices suitable for healthcare has led to the development of smart healthcare systems and suggests a new medical paradigm. As a result, there is a significant increase in the movement to accommodate changing health care concepts and analyses of measured biometric information using multiple measurement sensors are needed for ongoing healthcare. In order to provide rapid diagnosis and personalized diagnosis through the analyzed biometric information, a smart healthcare system with biometric technology is essential. In this paper, the goal is to store biometric information measured through multiple biometric sensors (blood pressure, heart rate, and body temperature sensors) in the DB using XBee sensors and then analyze stored biometric information through back-propagation algorithm, which is a neural network algorithm to derive the user's current state. As a result of the performance evaluation, the back-propagation algorithm for biosignal analysis showed an error rate of 2.96% on average and showed the lowest error rate when the window size was divided by 3000. In addition, the proposed system showed 87.6% accuracy through 700 performance evaluation data. It is expected that the proposed system will have high reliability and efficiency. The purpose of this study is to help the development of smart healthcare technology through researching the user-based service model and securing high quality data and contents based on smart healthcare using the proposed neural network based smart healthcare system.