Medical cyber-physical systems: A survey

Dey, Nilanjan; Ashour, Amira S.; Shi, Fuqian; Fong, Simon; Tavares, João Manuel R. S.

doi:10.1007/s10916-018-0921-x

Cited by 186 publications

(82 citation statements)

References 67 publications

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“…In the years to come, closed-loop medical devices, artificial intelligence, and networked medical instruments [353] will begin to emerge along existing medical robotics [354], [355]; and physiological closed-loop control systems will become visible within the clinical, home-care, and ambulatory environments. Ultimately, it is possible that many of these devices will be linked to an electronic health network, which could maintain critical patient data or even allow physicians to monitor and adjust treatment goals remotely.…”

Section: Discussionmentioning

confidence: 99%

Physiological Closed-Loop Control (PCLC) Systems: Review of a Modern Frontier in Automation

et al. 2020

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Over the past decade, there has been an unprecedented international focus on improved quality and availability of medical care, which has reignited interest in clinical automation and drawn researchers toward novel solutions in the field of physiological closed-loop control systems (PCLCs). Today, multidisciplinary groups of expert scientists, engineers, clinicians, mathematicians, and policy-makers are combining their knowledge and experience to develop both the next generation of PCLC-based medical equipment and a collaborative commercial/academic infrastructure to support this rapidly expanding frontier. In the following article, we provide a robust introduction to the various aspects of this growing field motivated by the recent and ongoing work supporting two leading technologies: the artificial pancreas (AP) and automated anesthesia. Following a brief high-level overview of the main concepts in automated therapy and some relevant tools from systems and control theory, we explore -separately -the developments, challenges, state-ofthe-art, and probable directions for AP and automated anesthesia systems. We then close the review with a consideration of the common lessons gleaned from these ventures and the implications they present for future investigations and adjacent research.

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Section: Discussionmentioning

confidence: 99%

Physiological Closed-Loop Control (PCLC) Systems: Review of a Modern Frontier in Automation

et al. 2020

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“…As CPS is being inserted into the health care innovation ecosystems worldwide, it is also evolving toward medical CPS (MCPS) (Depari et al, 2019;Dey et al, 2018). MCPS is expanding the capabilities in the phenomics and real-time predictive analytics knowledge domains in particular, not to mention access to Big Data that are user-and patient centric to enable digital health.…”

Section: Cyber-physical Systemsmentioning

confidence: 99%

The Big Picture on the “AI Turn” for Digital Health: The Internet of Things and Cyber-Physical Systems

Özdemir

2019

OMICS: A Journal of Integrative Biology

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This article offers an analysis of the ways in which digital health innovations are being coproduced by mainstreaming of artificial intelligence (AI), the Internet of Things (IoT), and cyber-physical systems (CPS) in health care. CPS blurs the boundaries between the physical and virtual worlds, and creates a dynamic digital map of all things in existence that can be analyzed in ways that are much more sophisticated than a bar code scanning system. Examples of CPS include self-driving cars, wearables for digital monitoring of heart arrhythmias, industrial AI-powered robots in smart factories and health robots delivering home care services to disabled persons and rural communities. Another interesting prospect of digital health powered by AI, IoT, and CPS is remote phenotypic data capture and characterization of pharmaceutical outcomes in clinical trials in ways that are user centric and meaningful to patients. For rural or remote communities with limited access to medical product information, the IoT could bring about pharmacy and health services innovation. There are unprecedented societal challenges at intersections of digital health with AI, IoT, and CPS as well. For example, the physical and virtual worlds markedly differ in speed, scale, and temporalities, as do our physical self and digital footprints. Our efforts to map and develop effective solutions to societal corollaries of AI, IoT, and CPS need to bear in mind such asymmetries between the physical and virtual worlds. A societal issue such as privacy may emerge in different forms and intensities in the physical and virtual contexts. Digital data are highly fluid and can rapidly move across spaces and places, whereas the physical data and humans are much slower and exist in different scales than our digital footprints. It is therefore timely for the system sciences and integrative biology communities to critically engage with digital health and the related technologies, such as AI, IoT, and CPS.

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“…CPS in medicine is a classic example of closed-loop feedback control systems. Application scenarios for such CPSs vary from patient monitoring, analgesic infusion pumps to implantation of sensory devices [13]. Any change of an object in the physical world can be directly modeled and improved on its counterpart in the cyber world, and in the physical world actions will be taken based on instructions from cyberspace CPS to control wind turbines [14] is used to reduce energy costs and increase profits.…”

Section: Related Workmentioning

confidence: 99%

Integration of Cyber-Physical Systems in EScience Environment: State-of-the-Art, Problems and Effective Solutions

Fətəliyev¹,

Mehdiyev²

2019

IJMECS

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The implementation of the concept of building an information society implies a widespread introduction of IT in all areas of modern society, including in the field of science. Here, the further progressive development and deepening of scientific research and connections presuppose a special role of e-science. E-science is closely connected with the innovative potential of IT, including the Internet technologies, the Internet of things, cyber-physical systems, which provide the means and solutions to the problems associated with the collection of scientific data, their storage, processing, and transmission. The integration of cyber-physical systems is accompanied by the exponential growth of scientific data that require professional management, analysis for the acquisition of new knowledge and the qualitative development of science. In the framework of e-science, cloud technologies are now widely used, which represent a centralized infrastructure with its inherent characteristic that is associated with an increase in the number of connected devices and the generation of scientific data. This ultimately leads to a conflict of resources, an increase in processing delay, losses, and the adoption of ineffective decisions. The article is devoted to the analysis of the current state and problems of integration of cyber-physical systems in the environment of e-science and ways to effectively solve key problems. The environment of e-science is considered in the context of a smart city. It presents the possibilities of using the cloud, fog, dew computing, and blockchain technologies, as well as a technological solution for decentralized processing of scientific data.

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Medical cyber-physical systems: A survey

Cited by 186 publications

References 67 publications

Physiological Closed-Loop Control (PCLC) Systems: Review of a Modern Frontier in Automation

Physiological Closed-Loop Control (PCLC) Systems: Review of a Modern Frontier in Automation

The Big Picture on the “AI Turn” for Digital Health: The Internet of Things and Cyber-Physical Systems

Integration of Cyber-Physical Systems in EScience Environment: State-of-the-Art, Problems and Effective Solutions

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