At the Business Innovation Exhibition 2026, students from Ajman University unveiled a new generation of healthcare solutions that aim to detect life-threatening conditions before symptoms even surface. Notably, these innovations reflect a broader shift in healthcare—from reactive treatment to proactive prevention—while also improving accessibility for underserved populations.
‘Pulse’ App Uses Everyday Data to Predict Cardiac Risk
One of the standout projects, Pulse, is an AI-powered mobile application developed by Nasima Helal and Jon Zaccary Regala. The tool analyses simple health inputs such as age, blood pressure, and other indicators to predict the likelihood of a heart attack.
Importantly, the students highlighted that heart attacks are often diagnosed only after symptoms appear, which limits timely medical intervention. Therefore, Pulse aims to bridge this gap by enabling early risk assessment. The prototype has demonstrated an accuracy rate of 98.3%, suggesting strong potential for both individual users and healthcare providers.
Moreover, the developers emphasised inclusivity. The app allows individuals to input their own health data, while clinicians can use it to assess patient risk and take preventive measures. Looking ahead, the team plans to collaborate with healthcare institutions and government bodies to refine the model using region-specific data.
‘DiaSens’ Targets Early Detection of Diabetic Neuropathy
In parallel, another student-led innovation, DiaSens, focuses on preventing severe complications in diabetic patients. Developed by Mohammed Wattar and Ali Hasan, the system aims to detect nerve damage—known as Diabetic Neuropathy—at an early stage.
This condition often reduces sensation in the limbs, meaning patients may not notice minor injuries. Consequently, untreated wounds can develop into ulcers, infections, or even lead to amputations. However, current diagnostic methods rely heavily on subjective responses, which can limit accuracy.
DiaSens addresses this challenge by using controlled vibration, pressure, and frequency to measure sensation thresholds precisely. As a result, the system produces consistent, quantifiable data rather than relying on yes-or-no patient feedback. Although the project remains in the prototype stage, early lab tests show promise, and clinical trials are expected next.
Shift Towards Preventive, Accessible Healthcare
Taken together, these student innovations signal a meaningful transition in modern healthcare. By prioritising early detection, both Pulse and DiaSens aim to reduce complications, improve patient outcomes, and lower long-term healthcare costs.
Furthermore, their focus on accessibility ensures that such tools could extend beyond hospitals to community clinics and screening programmes. As these technologies evolve, they could play a critical role in reshaping how healthcare systems identify and manage risk—well before conditions become critical.
