The system would provide medical advice and support for the first person to arrive on the scene of a road traffic accident. It would also continuously monitor and record the casualty’s condition before the arrival of emergency services.
The system – which is in its initial stages of development – is likely to be a small hand-held device that could be used by a doctor, nurse or paramedic and would work by gathering and analysing information from a sensor placed on the injured person’s body to measure their vital signs.
It would then ask the first person to arrive at the scene to input key information on the casualty to build a picture of their condition and give advice on the signs they should look for to determine the injured person’s condition and the action they should take to assist.
It would also store information on what has happened at the scene, which could then be passed onto the ambulance crew, then to the hospital, to ensure all crucial information is retained throughout the chain of events.
A team of clinicians, computing scientists and physiologists at the university are working together on the project. It is the first to be undertaken by dot.rural – the Aberdeen University research hub – funded by a £11.8m grant from the Engineering and Physical Sciences Research Council (EPSRC) under the Research Councils UK Digital Economy Programme, which is investigating how digital technologies could transform rural communities, society and business.
The research team plans to work with emergency services such as the British Association for Immediate Care, Scotland (BASICS Scotland) and to build on previous work carried out by Intelesens, a spin-out company from Ulster University that creates wireless monitoring devices.
Prof David Godden from Aberdeen University’s centre for rural health and Prof Chris Mellish from the university’s computing science department are leading the project.
Prof Godden said: ’The system would gather information on the casualty’s vital signs via a sensor placed on their body and information inputted by the person at the scene. This information would be analysed and advice would be provided on what should or should not be done in order to help the casualty.
’It would also constantly monitor the person’s condition and any change – a dramatic rise in heart rate for example – would signal an alert that action needed to be taken.
’In addition, the device would provide a record of information on the casualty’s condition from the moment the person arrives on the scene, meaning that all vital information gathered is retained and can be passed on accurately and promptly to the hospital’s medical team.’
Prof Mellish said: ’The system will use a technique called Natural Language Generation, where complex data is translated into simple and understandable text. The medical data gathered by the sensor and any actions that need to be taken would be communicated by the system through clear and concise sentences, making it simple for the first person on the scene to follow in what is likely to be a highly tense situation.’
Research into the system begins this month with the project running for three years.
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