Abstract
The significant increase in the number of individuals with chronic ailments (including the elderly and disabled) has dictated an urgent need for an innovative model for healthcare systems. The evolved model will be more personalized and less reliant on traditional brick-and-mortar healthcare institutions such as hospitals, nursing homes, and long-term healthcare centers. The smart healthcare system is a topic of recently growing interest and has become increasingly required due to major developments in modern technologies, especially artificial intelligence (AI) and machine learning (ML). This paper is aimed to discuss the current state-of-the-art smart healthcare systems highlighting major areas like wearable and smartphone devices for health monitoring, machine learning for disease diagnosis, and the assistive frameworks, including social robots developed for the ambient assisted living environment. Additionally, the paper demonstrates software integration architectures that are very significant to create smart healthcare systems, integrating seamlessly the benefit of data analytics and other tools of AI. The explained developed systems focus on several facets: the contribution of each developed framework, the detailed working procedure, the performance as outcomes, and the comparative merits and limitations. The current research challenges with potential future directions are addressed to highlight the drawbacks of existing systems and the possible methods to introduce novel frameworks, respectively. This review aims at providing comprehensive insights into the recent developments of smart healthcare systems to equip experts to contribute to the field.
Highlights
With projections of 22% of the population reaching the age 60 or more by 2050 [1], people affected by chronic diseases are growing along with health-related emergencies, resulting in a higher pressure on the healthcare industry [2], [3]
The goal of this paper is to explore the state-of-the-art smart healthcare systems that highlight the significant areas of research, including wearable and smartphone-based health monitoring, machine learning for predictive analytics, and assistive frameworks developed for assisted living environments, including social robots
OPEN DISCUSSIONS In this review, we have described smart healthcare frameworks highlighting areas such as health monitoring systems based on wearable devices and smartphones, disease detection using machine learning, utilizing Internet of Medical Things (IoMT) and social robots for ambient assisted living (AAL), and software integration architectures used to develop such assistive frameworks
Summary
With projections of 22% of the population reaching the age 60 or more by 2050 [1], people affected by chronic diseases are growing along with health-related emergencies, resulting in a higher pressure on the healthcare industry [2], [3]. The cost of said health care, medications, and medical devices continuously soar, making it harder to cover such costs for the average citizen as the need for more caregivers and healthcare facilities increases to with-stand the increase in demand [4]. Combined, these conditions call for cheaper, more inclusive, and better health care solutions. A great candidate for such a situation is utilizing the recent advancements in smart and miniaturized sensors, communication technologies, and artificial intelligence to provide technological solutions at an affordable price to the broadest range of the population without sacrificing the quality of care. More robust and advanced storage and processing capabilities provided by big data
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
