The use of artificial intelligence and robotics in regional anaesthesia

McKendrick, M., Yang, S. and McLeod, G.A. (2021) The use of artificial intelligence and robotics in regional anaesthesia. Anaesthesia, 76(S1), pp. 171-181. (doi: 10.1111/anae.15274) (PMID:33426667)

Abstract

The current fourth industrial revolution is a distinct technological era characterised by the blurring of physics, computing and biology. The driver of change is data, powered by artificial intelligence. The UK National Health Service Topol Report embraced this digital revolution and emphasised the importance of artificial intelligence to the health service. Application of artificial intelligence within regional anaesthesia, however, remains limited. An example of the use of a convoluted neural network applied to visual detection of nerves on ultrasound images is described. New technologies that may impact on regional anaesthesia include robotics and artificial sensing. Robotics in anaesthesia falls into three categories. The first, used commonly, is pharmaceutical, typified by target‐controlled anaesthesia using electroencephalography within a feedback loop. Other types include mechanical robots that provide precision and dexterity better than humans, and cognitive robots that act as decision support systems. It is likely that the latter technology will expand considerably over the next decades and provide an autopilot for anaesthesia. Technical robotics will focus on the development of accurate sensors for training that incorporate visual and motion metrics. These will be incorporated into augmented reality and visual reality environments that will provide training at home or the office on life‐like simulators. Real‐time feedback will be offered that stimulates and rewards performance. In discussing the scope, applications, limitations and barriers to adoption of these technologies, we aimed to stimulate discussion towards a framework for the optimal application of current and emerging technologies in regional anaesthesia.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Yang, Dr Shufan
• Authors: McKendrick, M., Yang, S., and McLeod, G.A.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: Anaesthesia
• Publisher: Wiley
• ISSN: 0003-2409
• ISSN (Online): 1365-2044
• Copyright Holders: Copyright © 2021 Association of Anaesthetists
• First Published: First published in Anaesthesia 76(S1):171-181
• Publisher Policy: Reproduced in accordance with the publisher copyright policy