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A student team from Institut Teknologi Sepuluh Nopember (ITS) has introduced Hemoglobest, a non-invasive haemoglobin detector integrated with artificial intelligence (AI) to predict and monitor anaemia in lupus patients. Lupus, an autoimmune disease, often manifests in complications like anaemia, necessitating a specialised approach. The Hemoglobest, equipped with an STM32 AI system, efficiently calculates haemoglobin levels and predicts the likelihood of anaemia, offering a novel tool for early detection.
Led by Muhammad Taufiqul Huda, the Institut Teknologi Sepuluh Nopember (ITS) Hemoglobest Team recognised the intricate challenges lupus patients face in detecting anaemia. Lupus patients typically exhibit lower haemoglobin levels than their non-lupus counterparts, rendering traditional detection methods less effective. Huda emphasised the potential damage to the cell structure of organs in lupus patients due to anaemia, underscoring the critical need for early warning systems to manage their health effectively.
The prevalence of anaemia in Indonesia is a significant public health concern, particularly among specific demographic groups. A study in Semarang found that 14.3% of pregnant women were anaemic, with factors such as inadequate nutrient intake and compliance with antenatal care guidelines being associated with the condition. In light of this, Taufiqul initiated the creation of a new innovation in detecting anaemia for Lupus patients.
The key innovation lies in using STM32 artificial intelligence, enabling the Hemoglobest to conduct calculations with remarkable efficiency. This expedites the prediction of anaemia conditions and serves as a power-saving microcontroller. The AI integration is particularly significant for lupus patients, providing a specialised approach to address their needs in haemoglobin level monitoring.
Unlike conventional haemoglobin detectors, the Hemoglobest employs a non-invasive procedure, eliminating the need for skin incisions and minimising discomfort. This feature ensures ease of use and pain-free monitoring, making it a more patient-friendly solution. Revelyno Rellert Towidjojo, a member of the Hemoglobest team, highlighted the simplicity and user-friendly nature of the device, a crucial factor in ensuring widespread adoption and accessibility.
The device utilises five light spectrums that are absorbed by haemoglobin in the blood vessels of the fingertips. This multi-spectrum approach enhances detection effectiveness compared to conventional oximeters, which typically use only two spectrums. The incoming light spectrum is received by sensors within the device and patterns in each spectrum are identified through detailed analysis. This enables the device to provide accurate readings of haemoglobin levels, distinguishing between oxygen-carrying and non-oxygen-carrying haemoglobin.
The implementation of a non-invasive haemoglobin detector also aligns with environmental considerations. Non-invasive devices like the Hemoglobest generate less medical waste than their invasive counterparts. This is a crucial aspect in reducing the environmental impact of medical procedures, as traditional methods often involve the use of disposable equipment and test strips, contributing to a significant amount of medical waste. Huda emphasised the potential positive impact of the Hemoglobest in reducing medical waste in Indonesia, aligning with global efforts towards sustainability.
The success of the Hemoglobest project can be attributed to the dedicated efforts of the entire team, guided by Astria Nur Irfansyah ST MEng PhD, a lecturer from the Electrical Engineering Department at ITS. Their commitment was recognised, and the project secured a silver medal in the Presentation category at the 36th National Student Scientific Week (Pimnas) in 2023. This achievement validates the innovation behind the Hemoglobest and highlights the importance of student-driven initiatives in advancing healthcare technology.
Astria emphasised that Hemoglobest represents a significant leap forward in the realm of medical technology, particularly in the context of autoimmune diseases like lupus. Integrating artificial intelligence, non-invasive procedures, and environmental consciousness positions this innovation as a beacon of progress in healthcare.
As the team continues to refine and expand the capabilities of the Hemoglobest, the potential impact on patient care and environmental sustainability remains promising. The successful amalgamation of technology, innovation, and dedication exemplified by the ITS Hemoglobest Team underscores the transformative power of student-led initiatives in addressing critical healthcare challenges.
