Predictive data regression technique based carbon nanotube biosensor for efficient patient health monitoring system

Abstract

In many ways, monitoring the patient's health with appropriate sensors to monitor the hospital’s connection, as if the patient is lying in bed. The previous method of monitoring can be uncomfortable for a variety of reasons. Tracking a growing number of patients requires many trained health professionals and doctors. The proposed predictive data regression technique (PDRT) based carbon nanotubes (CNT) biosensor system has been introduced in the fields like Biomedical. In this analysis technique, the sensor value is compared to the threshold value; if any changes occur, the controller sends the user alert via IoT. The patients are present in this area so that their physicians and many physiological measurements and applications can be seen. Carbon nanotubes (CNT) have been used as electronic mediators and adsorption substrates in biosensors due to their extraordinary electrochemical properties. Explore its potential biosensing applications, platinum, carbon nanomaterials, electrochemical electrode preparation and features. The purpose of this proposal is to maintain a system of inpatient physiological parameters and activity. The physician can see a graphical view of the patient's parameters and a computer system worn by the patient, the Wi-Fi network, and the display. Abnormalities inpatient data are messages sent to the doctor via an IoT system to remind them of the situation. The Proposed Predictive Data Regression Technology (PDRT) system is given a better performance to the user, and it provides the output accuracy.