Fuzzy Granular Decision Support for Ventilator Optimisation in Critically ill Patients using Electrical Impedance Tomography (EIT)

Lead Research Organisation: University of Sheffield
Department Name: Automatic Control and Systems Eng

Abstract

The care of critically ill patients requiring mechanical ventilation remains beset by the combined effects of critical illness and of the mechanical ventilation of the lung. Such effects are compounded by the lack of knowledge of the rate and time at which 'weaning' from the machine should occur. This project aims at developing an adaptive decision support system to assist ICU staff in the optimisation of ventilation and weaning processes. To help achieve this, an adaptive hybrid model which describes the patient-ventilator interaction during ventilation as well as weaning phases will be elicited. In addition to knowledge gathered through data relating to blood gases and lung expansions, the project aims at exploiting a revolutionary technique developed at sheffield, called Electrical Impedance Tomography (EIT) which consists of measuring, in a non-invasive fashion, the degree of expansion or collapse of the lungs and the effect of the ventilation strategy upon these. Two important aspects of this project relate to the inclusion of the EIT measurement technique to improve the monitoring of the patient's respiratory demands and to the use of granular computing for the hybrid model represented by the neural-fuzzy layer. The elicitation of such a model will form the basis for the design and development of an adaptive decision support system for optimal therapeutic advice on ventilator settings and weaning operation. On-line and off-line validation of the system in a series of ICU trials are envisaged.

Publications

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Denaï MA (2010) Absolute electrical impedance tomography (aEIT) guided ventilation therapy in critical care patients: simulations and future trends. in IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society

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El-Samahy E (2006) A closed-loop hybrid physiological model relating to subjects under physical stress. in Artificial intelligence in medicine

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M Denai (2009) Assessment of Lung Collapse with Electrical Impedance Tomography in British Journal of Anaesthesia

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Nunes C (2006) Fuzzy modelling for controlled anaesthesia in hospital operating theatres in Control Engineering Practice

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Qing Lu (2010) A model-free self-organizing fuzzy logic control system using a dynamic performance index table in Transactions of the Institute of Measurement and Control

 
Description 1. developed Electrical Impedance Tomography (EIT) technique for lung imaging in Intensive Care Unit (ICU) for critically-ill patient;

2. Used the information provided by the images to design a decision support system that administers therapy to ICU patients to help them breath on their own.
Exploitation Route The findings can be exploited in two-fold:

1. Use the electronic system based around Electrical Impedance Tomography (EIT) to develop a portable system that takes images of the patient lungs in a flexible and economic way;

2. Embed this EIT-based imaging system within a more integrated architecture that advises on 'optimal' therapy for ICU patients.
Sectors Education

Electronics

Healthcare

 
Description The research findings relate mainly to the exploitation of Electrical Impedance Tomography (EIT) (a Sheffield University invention) in General Intensive Care Unit (ICU) as an effective tool for decision support in cases of sepsis, We have indeed devised a portable decision support system which uses intelligent system technologies to administer 'optimal' therapy to critically-ill patients. The findings also provided gearing towards 2 more EPSRC sponsored research for treating critically-ill patients in ICU and Cardiac ICU>
First Year Of Impact 2012
Sector Electronics,Healthcare
Impact Types Societal

Economic

Policy & public services

 
Description LIDCO Ltd 
Organisation LIDCO Ltd
Country United Kingdom 
Sector Private 
PI Contribution Informatics
Collaborator Contribution Knowledge, data, specific algorithms for communication
Impact Papers
 
Description Northern General Hospital 
Organisation Northern General Hospital
Country United Kingdom 
Sector Hospitals 
PI Contribution This project made clinical staff technology aware in terms of informatics and electronics
Collaborator Contribution clinical know how, data, knowledge in general.
Impact NO specific one other than joint papers.
Start Year 2006
 
Description Royal Hallamshire Hospital 
Organisation Royal Hallamshire Hospital
Country United Kingdom 
Sector Hospitals 
PI Contribution Staff more aware of informatics based research
Collaborator Contribution Data, knowledge
Impact No specific outputs other than joint papers
 
Title Neuro-Fuzzy Systems 
Description 1. Electrical Impedance Tomography for use in Lung Imaging in ICU 2. Decision Support System in ICU using EIT and Machine Learning and Control Systems 
IP Reference  
Protection Protection not required
Year Protection Granted
Licensed No
Impact the algorithms hence designed via this project have provided the necessary gearing towards other grant research outputs, EPSRC or otherwise in a multi-disciplinary fashion.