A Survey on Ambient Intelligence in Healthcare

TLDR

Ambient Intelligence (AmI) is a paradigm of adaptive digital environments that sense human needs, gestures, and emotions, enabling pervasive, unobtrusive interactions and making it a promising technology for healthcare solutions. This survey reviews the emergence of AmI techniques in healthcare, aiming to provide background and explore how the technology can support individuals with physical or mental disabilities and chronic diseases. The authors examine the infrastructure—smart environments and wearable medical devices—alongside AI methods such as learning, reasoning, and planning, and discuss case studies that illustrate current practice and future research challenges. The survey highlights successful case studies and identifies current and future challenges, outlining potential research paths for advancing AmI in healthcare.

Abstract

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.