A Novel Neural Classification Vector Machine (NCVM) For IOT Based Health Care Monitoring System

Abstract

Today, IoT (Internet of Things) is used in many applications. Some of the applications of IoT are smart parking, smart homes, smart cities, smart environments, industrial sites, agricultural fields, and health monitoring processes. One of such applications is monitoring patient health status through IoT in the healthcare field, improving the efficiency of medical teams by monitoring patient health status in real-time, where sensors acquire data from patients and reduce human errors. So far we have seen a health monitoring system that collects basic parameter information such as heartbeat, body temperature, blood pressure, and growth parameters. In this paper, we discuss monitoring of patient brain signals and real-time detection of patient status. To collect data from brain signals, we used Neurosky Mindwave mobile headsets powered by EEG technology. Display the output result in waveform mode. Display the output result in waveform mode. The remote monitoring system is geared toward people with intellectual disabilities and provides regular updates on the health status of caregivers while they are at work. It also reduces the workload for patients by staying at home rather than going to hospital to check their details. If the system recognizes any changes in the patient's heart rate, brain signal, or body temperature, the system will alert the doctor and corresponding family members of the patient's condition through the Internet of Things, and store the patient's detailed information in the cloud