AN OVERVIEW OF PATIENT MONITORING SYSTEMS BASED ON MACHINE LEARNING IN THE INTERNET OF THINGS
Abstract - The Internet of Things (IoT) is widely used in many applications including patient monitoring systems. The purpose of healthcare systems is to monitor the patient in order to prevent risks, deal with critical cases quickly, and to establish long-distance communication for remote treatments. The Internet of Things has a long-term impact on patient monitoring, patient management, patient’s physiological information, and critical care. The sensors are connected to the patient to collect the data which are first sent to system controls and then autonomously to healthcare providers. There are a variety of biosensors that send the medical information to mobile applications or websites via wireless network. Healthcare providers are thus enabled to monitor the patient and control the treatment outside of hospital walls, therefore; the IoT medical devices require accurate methods of patient monitoring in order to predict the patient’s condition more precisely, and to increase the efficiency of the network. An overview of patient monitoring systems based on machine learning in the Internet of Things is provided in the following article.
Keywords - IOT, Machine Learning, HealthCare, WBAN