The increasing use of electronic devices in Rwanda’s modernising healthcare sector highlights the urgent need for reliable Electromagnetic Compatibility (EMC) monitoring systems. On September 6, the University of Rwanda hosted a workshop attended by over 50 biomedical engineers, healthcare professionals from various hospitals, and aspiring students. The event, held at the College of Science and Technology (CST-UR), aimed to showcase a newly developed device based on IoT for monitoring and a machine-learning-powered prediction algorithm designed for real-time and remote monitoring of Electromagnetic Compatibility (EMC) from Biomedical devices. The workshop was organised to share key findings and raise awareness about the results of a grant project titled ‘Electromagnetic Compatibility Monitoring and Prediction Models for Biomedical Devices (EMC-MPM)’. ALSO READ: University of Rwanda’s newly developed device for real time and remote of EMC monitoring and prediction. This project, funded by the International Centre of Insect Physiology and Ecology (ICIPE) through the Regional Scholarship and Innovation Fund (RSIF), runs from 2022 to 2024. Electromagnetic compatibility (EMC) is a critical concern in hospitals, where electronic medical devices are in constant use. Uncontrolled emission of electromagnetic waves from biomedical devices can pose serious health risks, including cancer, mental disorders, and skin conditions, making it a significant public health issue. Recognising these dangers, the EMC-MPM project was initiated to address the risks through the use of cutting-edge technology. The project aims to develop an Internet of Things (IoT) based device to monitor EMC levels and a machine learning-driven algorithm to predict emissions from medical devices. This will allow hospitals to proactively manage these emissions and ensure the safety of patients and staff. The role of IoT and machine learning One of the most exciting aspects of this project is its use of IoT technology for real-time and remote monitoring of radiation from biomedical devices. IoT, known for its cost-effectiveness and ability to provide real-time data, is combined with machine-learning algorithms to predict electromagnetic emissions before they reach dangerous levels. Sensors will be installed on select biomedical devices to monitor field strength, voltage fluctuations, frequency, and other key parameters related to electromagnetic emissions. This data will then be analysed and compared to international safety standards. The system aims to provide hospital management with critical information for better maintenance and planning of medical equipment, ultimately helping to avoid unexpected breakdowns or dangerous emissions. Omar Gatera, a senior lecturer in the Department of Electrical and Electronics Engineering at the School of Engineering, CST-UR, and the Head of Ph.D. Studies and Research at the African Centre of Excellence in Internet of Things (ACEIoT), as well as the Principal investigator of the project, explained that the newly developed device is designed to ensure the safety of individuals around it by protecting them from harmful electromagnetic radiation. He noted: “We believe electromagnetic radiation can affect human health and interfere with the accuracy of biomedical devices. That’s why we developed this new device to monitor and predict electromagnetic radiation, preventing harm to people and ensuring accurate results from biomedical devices. “This is a new innovation in the Rwandan market,” he continued, affirming that the device’s main contribution is to make existing devices smarter and ease the work of biomedical engineers in healthcare facilities. One of the participants, Saphina Niyonkuru, a biomedical engineer at the University Teaching Hospital of Kigali (CHUK), said the workshop was highly impactful. She noted that, as technicians, they previously operated machines emitting radiation manually. Now, with the new device, they will be able to measure radiation levels in real time, ensuring safety for both technicians and patients. “This device will help us measure the radiation capacity, which will ultimately improve the accuracy of the results we provide. It will also protect us from unnecessary radiation exposure, as well as safeguard patients,” she explained. Niyonkuru added, “In the past, we could enter a radiotherapy room without checking the radiation levels. With this device, we’ll be able to assess the room first to ensure it’s safe. Its introduction is timely.”
