Stroke is still a major health problem in Indonesia and the world. Early monitoring and intervention as stroke prevention efforts have not received special attention in the community. Universitas Brawijaya students come up with technology as an effort to prevent hypertension and hypercholesterolemia for stroke sufferers based on IoT using machine learning methods.

The stroke itself is an acute clinical event associated with cerebral circulation disorders. The main risk factors for stroke are high blood pressure, high blood cholesterol levels, and high blood glucose levels. The increase in stroke mortality and morbidity is due to the lack of early monitoring and intervention in sufferers.

Inspired by this phenomenon, five students of Universitas Brawijaya through the Karsa Cipta Student Creativity Program (PKM-KC) were intrigued to create a prototype called E-dection.

Under the guidance of Ir. Nurussa’adah M.T., this team consists of M. Dwi Nur Afini (FT’20), M. Romadhoni P. (FT’20), Made Ananta W. (FT’19), Ayu Cetiya M. (FIKes’19), and Abhimanyu Awanda R. (FK’19).

E-dection consists of a smart band and a smart pillow that can provide monitoring functions and early independent intervention.

Indicators that can be monitored using E-dection are blood pressure and cholesterol levels as well as blood glucose non-invasively.

The independent intervention used in this prototype is heat therapy to reduce the amount of cholesterol in the blood.

Dr. Ir. Dewa Gede Raka Wiadnya, M.Sc., as one of the users revealed that E-dection can be applied to the general public, especially to people with a history of mild stroke.

E-dection can reduce examination costs because it is equipped with a non-invasive monitoring system and therapy to lower cholesterol levels.

In the E-Dection application, there is also telemonitoring for the doctor in charge to facilitate consultation regarding the condition of the user, explained Dr. Dewa when met at his workplace, Monday, August 1, 2022.

“It’s comfortable when I use the smart pillow, it warms my neck. I like its ergonomic shape, hopefully, it can reduce the prevalence of severe stroke by using this tool,” he said.

E-dection is an IoT-based prototype that is connected to the application. This application is useful for categorizing patient conditions using machine learning methods and making it easier to use simple prototypes.

This innovation is expected to reduce the prevalence of morbidity and mortality caused by stroke.