In Australia, stroke is among the leading causes of death and permanent disability. Some 5 per cent of deaths are due to stroke, while strokes cost the Australian healthcare system $6.2 billion annually.
Strokes occur when there’s a sudden loss of blood flow in the brain. This prevents the brain tissue from getting the oxygen and nutrients it needs, which can lead to damage to sections of the brain.
Timely stroke treatment can limit brain damage and improve outcomes for patients. But this depends on early recognition of the symptoms, which is not always easy.
Our team has developed a new smartphone app to screen a person’s facial expressions and detect whether they’ve had a stroke. We’ve recently published the results of a pilot study of this tool, and found it could identify if someone has had a stroke quickly and relatively accurately.
Scanning facial expressions
One of the earliest external symptoms of stroke can be found in facial expressions such as droop, where one side of the mouth is not activated when a person tries to smile.
However, paramedics responding to emergencies and hospital emergency department staff often miss stroke cases. Facial expressions are naturally different between people, and identifying subtle changes in a high-stress environment is challenging. This can become even more difficult if the patient is from a different ethnicity or cultural background.
With our smartphone app, a paramedic or other first responder asks the patient to try to smile, and ‘films’ the patient’s face while they do so. An AI-based model then analyses the video recording, looking for similar signs as used by clinicians to identify stroke, namely the asymmetrical drooping of the mouth.
The app is designed for simplicity – the user just has to point the camera at the patient and press a button. To ensure the patient’s privacy, the video is analysed in real time and does not have to be stored. This device would only need a smartphone, so would be easy to deploy, and would be a cost-effective solution.
The idea is that first responders such as paramedics or nurses in the emergency department would have this app on their smartphones. When they first see a patient who has experienced a medical emergency, they can use the app to detect in seconds whether the patient may have suffered a stroke. That way, treatment can be fast-tracked accordingly.
Our pilot study
We tested the tool on a small dataset, using video recordings of 14 people who had experienced a stroke, and 11 healthy controls.
We found it was 82 per cent accurate, meaning it correctly identified a stroke 82 per cent of the time. Our tool is not designed to replace comprehensive clinical diagnostic tests for stroke, but it could help identify people needing treatment much sooner and assist clinicians.
While these results are promising, we’re planning to continue to optimise the model. Our hope is that the accuracy will improve as we build a bigger dataset, with recordings of more patients.
At this stage, the AI model has only been trained and developed on a small dataset, and the data lacks diversity in ethnicity and demographics. It will be essential to refine and test the app for people of different cultural and ethnic backgrounds.
Down the track, we plan to partner with clinicians, emergency departments and ambulance services to conduct clinical trials. We’ll need to test the effectiveness of this tool in the hands of the actual users, such as paramedics, to confirm it helps them look after their patients.
Dinesh Kumar, Professor, Electrical and Biomedical Engineering, RMIT University; Guilherme Camargo de Oliveira, PhD Candidate, School of Engineering, RMIT University; Nemuel Daniel Pah, Visiting Associate Professor, STEM College, RMIT University, and Quoc Cuong Ngo, Research Fellow, School of Engineering, RMIT University
This article is republished from The Conversation under a Creative Commons licence. Read the original article.
Do you have a family history of strokes? Would you be interested in using an app like this? Let us know in the comments section below.
Also read: Five health conditions that can mimic stroke symptoms
This app sounds like it would help quite a few people. The only thing is you actually have to get to the hospital first. There is no guarantee that an ambulance or the specially trained paramedics in normal cars will actually respond in an appropriate time. With all of the ambulance ramping and call outs for more minor ailments (where family should take them to the ER in a car) this means more time critical patients stroke/heart, etc can hopefully be assessed and taken to the hospital in a timely manner. There have also been cases where the operator hasn’t really taken notice of what the symptoms are over the phone and in one case I know of thought it was just someone who had taken drugs.