A Survey on Ambient Intelligence in Healthcare

Abstract

Ambient intelligence (AmI) is a computing paradigm wherein conventional input and output media no longer exist. Instead, sensors and processors are integrated into conventional objects that harmonize with people in their living situations. AmI relies on artificial intelligence (AI) to perform these duties. It obtains contextual information from embedded sensors, interprets it, and adapts the environment to interpreted needs. AmI is context-aware, personalized, anticipatory, adaptive, ubiquitous, and transparent to the user. As an intelligent paradigm, it builds upon traditional AI foundations (reasoning, activity recognition, decision making, spatiotemporal logic) and adds advances from other fields: data collection via sensor networks, robotics, and human/-computer interactive interfaces.AmI offers many enticing solutions for a healthcare domain that is beset by problems such as lack of sustainability and cost inefficiencies. Existing solutionsVweb-based platforms, electronic health records, smartphone apps for physiological monitoringVare hampered by scalability problems, security risks, and privacy issues, and none of them offer a continuous view of conditions spanning many years. Recent advances in sensor networks are spearheading revolutions in low-cost healthcare monitoring systems in homes and living environments. Common applications would include monitoring the status of patients with chronic diseases, assistive care, persuasive services for encouraging healthier lifestyles, rehabilitation, and support for healthcare professionals through improved communication and monitoring tools.The supporting infrastructure and technologies used in AmI systems for healthcare break into two main categories: body area networks (BANs) and dense/mesh sensor networks in smart homes. In addition, recent trends in sensor networks are driving new developments in epidermal electronics and microelectromechanical system (MEMS) sensors.In BANs, sensors are attached to clothing or the body itself, enabling continuous monitoring of heartbeat, temperature, physical activity, blood pressure, electrocardiogram, electroencephalography, and electromyography. The infrastructure can remotely stream data to a doctor's site, so a diagnosis can be made in real time. Data can be stored in a medical database and link to emergency alerts and intelligent management. The networks are efficient and cost effective. Sensors consume little power and their batteries are long lasting. As sensors get mass produced, costs will scale downward. BANs, moreover, can interface with a wide variety of network infrastructures. It is useful to think of BANs as being composed of three layers or tiers of communication from low level to high level: intra-BAN (2-m radio range), inter-BAN (body to access points communication), and beyond-BAN (streaming body sensor data to metropolitan areas via a gateway device).In dense/mesh sensor networks, processors and ambient sensors are embedded in everyday objects (clothes, household devices, furniture) to enable unobtrusive, ...

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