Abstract
Automation empowers self-sustainable adaptive processes and personalized services in many industries. The implementation of the integrated healthcare paradigm built on Health 4.0 is expected to transform any area in medicine due to the lightning-speed advances in control, robotics, artificial intelligence, sensors etc. The two objectives of this article, as addressed to different entities, are: i) to raise awareness throughout the anesthesiologists about the usefulness of integrating automation and data exchange in their clinical practice for providing increased attention to alarming situations, ii) to provide the actualized insights of drug-delivery research in order to create an opening horizon towards precision medicine with significantly improved human outcomes. This article presents a concise overview on the recent evolution of closed-loop anesthesia delivery control systems by means of control strategies, depth of anesthesia monitors, patient modelling, safety systems, and validation in clinical trials. For decades, anesthesia control has been in the midst of transformative changes, going from simple controllers to integrative strategies of two or more components, but not achieving yet the breakthrough of an integrated system. However, the scientific advances that happen at high speed need a modern review to identify the current technological gaps, societal implications, and implementation barriers. This article provides a good basis for control research in clinical anesthesia to endorse new challenges for intelligent systems towards individualized patient care. At this connection point of clinical and engineering frameworks through (semi-) automation, the following can be granted: patient safety, economical efficiency, and clinicians' efficacy.
Highlights
Is anesthesia management prone to error? Can one believe that such a standard procedure is applied optimally as a familiar routine OR, on the contrary, with major risks due to patient inter- and intra-variability? Either way, there is room for improving the anesthesia optimization and decrease the risks for the patients.Driven by societal challenges, the fast progress of advanced technology has been finding scalability to manyThe associate editor coordinating the review of this manuscript and approving it for publication was Nasim Ullah .applied industries
The complex procedure of general anesthesia can be computer-assisted in clinical practice; the high system complexity needs to be undertaken in terms of suitable modelling of multiple-input multiple-output (MIMO) interactions and stable control with feedback from multiple variables; robustness simulation should deal with the already studied intra-patient and inter-patient model variability and uncertainty, and with the additional bolus in the loop and surgical stimulation
MIMO strategy is the closest to clinical practice, as multiple drug doses are optimally infused in the patient based on specific output measurement; opioid-analgesia balance requires a direct measure of the specific analgesic effect, so an analysis of the current available commercial nociception devices should be done
Summary
Is anesthesia management prone to error? Can one believe that such a standard procedure is applied optimally as a familiar routine OR, on the contrary, with major risks due to patient inter- and intra-variability? Either way, there is room for improving the anesthesia optimization and decrease the risks for the patients.Driven by societal challenges, the fast progress of advanced technology has been finding scalability to manyThe associate editor coordinating the review of this manuscript and approving it for publication was Nasim Ullah .applied industries. Can one believe that such a standard procedure is applied optimally as a familiar routine OR, on the contrary, with major risks due to patient inter- and intra-variability? There is room for improving the anesthesia optimization and decrease the risks for the patients. The fourth industrial revolution’s effects on the future of health and well-being are translated into the emerging extension named Health 4.0 [1]. This process is empowered by adaptable cyber physical systems (CPSs), that integrate computation and physical entities through communication infrastructure. The fusion of technologies across physical, digital and biological areas resides at the core of health sector performance and has a transformative impact on drug delivery control systems.
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