Embedded AI-Based Digi-Healthcare

Abstract

Healthcare is an indispensable part of human life and chronic illnesses like cardiovascular diseases (CVD) have a deeply negative impact on the healthcare sector. Since the ever-growing population of chronic patients cannot be managed at hospitals, therefore, there is an urgent need for periodic monitoring of vital parameters and apposite treatment of these patients. In this paper, an Internet of Medical Things (IoMT) -based remote patient monitoring system is proposed which is based on Artificial Intelligence (AI) and edge computing. The primary focus of this paper is to develop an embedded prototype that can be used for remote monitoring of cardiovascular patients. The system will continuously monitor physiological parameters like body temperature, heart rate, and blood oxygen saturation, and then report the health status to the authenticated users. The system employs edge computing to perform multiple functionalities including health status inference using a Machine Learning (ML) model which makes predictions on real-time data, alert notifications in case of an emergency, and transferring data between the sensor network and the cloud. A web-based application is developed for the depiction of raw data and ML results and to provide a direct communication channel between the patient and the doctor. The ML module achieved an accuracy of 96.26% on the test set using the K-Nearest Neighbors (KNNs) algorithm. This solution aims to address the sense of emergency due to the alarming statistics that highlight the mortality rate of cardiovascular patients. The project will enable a smart option based on IoT and ML to improve standards of living and prove crucial in saving human lives.

Balancing Technological Advances with User Needs: User-centered Principles for AI-Driven Smart City Healthcare Monitoring

“…2) AI-driven monitoring system in smart healthcare: AIdriven monitoring systems have attracted researchers' attention due to their significant impact on people's lives. There have been numerous research studies [33], [43], frameworks [44], [45], [46] and services [8], [36] that focus on integrating artificial intelligence for smart healthcare. Table I summarizes the development of health monitoring systems considering the healthcare context, the invention, and AI technology.…”

“…Researchers in [8] used IoT and AI to remotely monitor cardiovascular patients using a device that allows for smart monitoring of human vitals such as body temperature, heart rate, oxygen levels. In [36], the authors suggest a smart home healthcare monitoring system where installed sensors and devices can meet the needs of elderly people for continuous care at home.…”

“…According to research, user-centered AI monitoring systems have the potential to transform the health industry by providing real-time health monitoring and support to patients [26], [59]. Using artificial intelligence technology, healthrelated data such as vital signs, physical activity levels, and sleep patterns can be automatically collected, analyzed, and used to detect health-related issues [8], [49].…”

“…1) Personalized health monitoring: These systems use AI technologies to collect, process, and analyze health-related data, allowing for personalized health monitoring and support to the users. The automatic collection of data, such as vital signs, physical activity levels, and sleep patterns, can help detect health-related issues in real-time [8], [49], [61], [69].…”

“…It can reduce the need for medical intervention [5], will rely less on traditional physical health facilities like hospitals and long-term care centers, and will be more individualized as a result. Numerous studies have been conducted on smart healthcare to monitor patient health, for example, Parkinson's disease [6] and mental health [7] and cardiovascular disease [8]. However, to maximize the benefits of AI-driven monitoring systems in smart city healthcare, it is crucial to adopt a user-centered approach.…”