According to WHO data from 2019, 18 million people live with rheumatoid arthritis (RA). This incurable disease requires long-term treatment and management for those affected.
As a chronic systemic autoimmune inflammatory disease, RA can significantly impact the quality of life, daily activities, and social engagement due to the inflammation and structural damage it causes to joints and bones.
This inflammation often leads to pain, swelling, and permanent joint damage. RA symptoms and causes are often undetected, making diagnosis delayed, and many people in Indonesia are still unaware of RA and have limited access to early diagnosis at healthcare facilities.
The discovery of an accurate early detection tool allows for earlier intervention, slowing disease progression and improving the quality of life for RA patients.
A team of UGM students has developed an innovative early detection tool for RA to reduce the number of RA patients annually.
Their tool uses infrared thermography technology to monitor heat distribution in the palms, supported by machine learning technology to enhance diagnostic accuracy.
The team consists of Awaliya Shabrina, a student from UGM’s Faculty of Engineering (FT UGM), along with four of her colleagues: Laila Nur Rizqi Tasnimiyah, Javana Avita Prameswari, Amir Fren Afrizal, and Muhammad Irfan, under the guidance of Dr. Prapto Nugroho.
Shabrina explained that previous studies have indicated that RA examinations still rely on invasive and large-scale equipment.
As a result, she and her team took the initiative to design an RA diagnostic prototype that can be used anywhere and anytime.
“Delayed diagnosis of RA can lead to a decline in quality of life, even permanent disability. One of the causes is late diagnosis and a lack of knowledge and information about the disease,” she stated.
Furthermore, Shabrina revealed that the prototype is named ReuMate, a tool for the early detection of rheumatoid arthritis using machine learning integrated with a mobile app.
The development of this non-invasive and portable RA early detection prototype, which integrates infrared thermography and machine learning methods, is essential for improving the accuracy of RA detection in the palms and providing educational information on managing and preventing the disease.
Additionally, the tool includes easily accessible educational resources related to RA management and prevention.
“The design of this prototype is beneficial for assisting in the early detection of RA in a non-invasive manner, enabling rapid treatment to prevent the condition from worsening, monitoring treatment, and providing education for RA patients through the mobile app,” she said.
Shabrina said the ReuMate innovation improves access to healthcare services, especially in remote areas, and significantly contributes to achieving the Sustainable Development Goals (SDGs).
By enabling early detection of RA, ReuMate facilitates more effective treatment and improves the quality of life for those affected.
“This prototype can be used in various healthcare facilities across Indonesia, including in remote areas, as it is easy to carry,” she explained.
Author: Agung Nugroho
Post-editor: Afif