An Intelligent Healthcare System for Quadriplegia Patients using Internet of Things and Machine Learning

Abstract

Quadriplegia is a severe medical condition that often leaves individuals with limited or no motor functions in all four limbs, significantly impacting their quality of life and independence. In recent years, advancements in Internet of Things (IoT) and Machine Learning (ML) technologies have opened new possibilities for improving the healthcare and quality of life for quadriplegia patients. This research presents an innovative Intelligent Healthcare System (IHS) designed to address the unique needs of quadriplegia patients by leveraging IoT and ML technologies. The proposed system consists of a network of interconnected IoT devices and sensors strategically placed in the patient's environment, such as their home or care facility. In this paper, we proposed a IoT based health care system which consists of accelerometer + gyro sensor and IR sensor with NodeMCU ESP8266 module. Our goal is to develop a system which should be easy to use and should be affordable. These sensors continuously monitor various aspects of the patient's health, including vital signs, environmental conditions, and movement patterns. The collected data is transmitted in real-time to a central processing unit, where sophisticated ML algorithms are employed to analyze and interpret the information.