Programme led by
Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland
Primary Investigator: Alan Smeaton (DCU)
Assistance dogs are often used by those with physical conditions to support their daily lives, and we know that they become highly attuned to their owner’s behaviours. Some dogs are known to be able to detect the onset of an epileptic seizure by their owner and can be trained to communicate to the outside world their detection of the onset of a seizure via a signalling behaviour such as doing spins, or rollovers.
Wearable sensors can provide us with data on our heart rate and activity intensity for example. When we apply machine learning and other AI techniques to raw data from wearables then we can get higher level interpretations such as step counts, caloric expenditure or recognition of activity types like walking, running, swimming, etc. In recent work I have used wearable accelerometers on the collars of trained dogs and used the data to automatically classify the dog’s activities into spinning or rollovers, exactly the kind of signalling behaviour used by assistance dogs. The accuracy of the automatic detection is already quite good but could be improved further.
I would like to combine simple sensors worn by assistance dogs to automatically detect their trained signalling behaviours to their human charges, in particular to the onset of an epileptic seizure and to do this in real time. The idea brings together patient needs for those with epilepsy, animal behaviour of assistance dogs, and machine learning and data analytics for automatic detection of dog behaviour. For this work I can bring in clinical expertise from the National Epilepsy Programme at Beaumont Hospital, practical expertise and access from a charity which breeds and trains assistance dogs, and the support of Epilepsy Ireland.
The project brings together a broad spread of research areas and it is not necessary that a successful applicant will have expertise in all of these areas
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