A novel healthcare framework for ambient assisted living using the internet of medical things (IOMT) and deep neural network

Abstract

The newest developments in the IoMT, wearable devices, and communications systems to offer smart healthcare services have made human life in the age of pervasive computing wiser. The healthcare sector may transform thanks to IoMT. Through software and Information Communication Technology (ICT), IoMT links wearable devices, patients, healthcare professionals, and careers. Ambient Assisted Lifestyle (AAL) allows it to incorporate new technology into day-to-day activities. Edge computation and cloud technologies are essential to achieving this goal to meet the needs of smart medical infrastructures. In this research wok, the IoMT-AAL architecture in the edge computing-assisted IoMT system based Deep Neural Networks (DNN) is presented in this study. The proposed IoMT-AAL aims to speed up timely data collecting and processing so that judgments are made utilizing the data. The IoMT-AAL model is used to identify the patient via the IoMT sensors, sending the data they have collected to edge computation. Then, many empirical analyses are conducted, and the outcomes are examined from many angles. It can be said that the IoMT-AAL effectively predicts the healthcare framework using DNN based on various parameters like specificity, precision, improvement, physical activity, tracking, and security. The simulation results demonstrated the IoMT-AALmodel's advantages over the other techniques.

Keywords

• Internet of medical things
• Healthcare system
• Wearable sensors
• Machine learning