The invention of Professor Samira A. Rahimi was selected as one of the 11 winning projects in the Défi Innover competition to counter Roche Canada’s COVID-19. It will be tested next month with around sixty patients in Quebec and Ontario, for a period of three to six months.
In the two provinces, between 70 and 80 percent of deaths from coronavirus occurred in seniors’ care centers, said Rahimi.
“We wanted to find a way to quickly identify the people who have COVID-19 in these establishments,” she explained. With artificial intelligence, you can monitor vital signs in real time. ”
The program “AiCoV19: AI-empowered Real-time COVID-19 Symptom Monitoring and Prediction among Senior Residents” by Ms. Rahimi exploits artificial intelligence and what is called the “Internet of medical objects”. Wearable technologies, such as bracelets and other sensors, and computer networks are connected via the internet to generate real-time interaction between beneficiaries and caregivers.
The project therefore makes it possible to follow, monitor and predict symptoms and asymptomatic changes in the elderly. The device alerts caregivers when symptoms of COVID-19 are detected and / or predicted, and remains alert for any signs of decompensation.
For example, if the data indicates a change or deterioration in vital signs, such as a fever or shortness of breath, the intelligent system will inform those responsible.
“The data collected is automatically transmitted to the platform. Everything is done in real time, said Rahimi. In the platform, we analyze the data (…) with artificial intelligence and we can send an alarm to the nursing staff to tell them that something is wrong. ”
Keeping seniors at home
The usefulness of the device is not limited to the fight against the coronavirus, however, since Ms. Rahimi believes that technology could be exploited to help keep seniors at home.
“We could also use this to monitor the health of people at home,” she said. It would be very useful in telemedicine. (…) With artificial intelligence, we can predict if something might go wrong, for example the next day or the following week. ”
–
