The June meetup of the Software Developers Cartel featured Kimberly Branan, a Biomedical Engineering Ph.D. candidate at Texas A&M University developing wearable technology to monitor cardiac and diabetes biomarkers continuously and noninvasively, aiming to provide access to healthcare for underserved populations. Kimberly works under the supervision of Dr. Gerard Coté in the Optical Biosensing Laboratory (OBSL).
Wearable biomedical devices coupled with appropriate algorithms, including advanced signal processing and artificial intelligence (AI), represent a transformative advancement in healthcare, offering real-time health monitoring and the potential for personalized medicine. These devices, which include wrist straps, rings, upper armbands, and patches, provide continuous data on various physiological parameters such as temperature, heart rate, heart rate variability, cuffless blood pressure, respiration rate, oxygen saturation, and cardiac output. Accelerometers and gyroscopes can also be added to the wearables and provide contextual awareness. Their applications span from fitness and wellness tracking to managing chronic diseases and enabling remote patient monitoring.
One of the most promising applications we will discuss is in non-invasive hypoglycemia detection, which is particularly beneficial for diabetes management. By continuously and noninvasively tracking the raw waveforms from signals coming from such wearables, we can extract features using AI algorithms like deep learning to predict hypoglycemic events without the need for continuous glucose monitoring or frequent finger pricks to obtain glucose values. These noninvasive wearable devices, coupled with AI, can then help individuals with diabetes maintain better glycemic control, potentially reducing the risk of complications. The future of wearable biomedical devices looks promising, with advancements in sensor technology, data analytics, and artificial intelligence likely to enhance their accuracy, functionality, and integration into comprehensive health management systems, ultimately improving patient outcomes and quality of life.
