The 2024 Senior Capstone course in biomedical engineering was taught by Yantao Shen. To learn more about the biomedical engineering projects, please email Yantao Shen.
From electromagnetics to biosensors to smart grids, we're on the cutting-edge of electrical and biomedical engineering research and training our students to be successful leaders in the field. Visit the Department of Electrical & Biomedical Engineering.
Explore biomedical engineering projects.
Students: Abigail Ganze, Natasia Ehlers, Zoe Atherton, Monserratt Ramirez
Howler Technology is a wearable, noninvasive monitoring system designed to detect early signs of heat stress in working dogs operating in high-risk environments such as military, law enforcement, search and rescue, and agricultural settings. Working dogs face extreme temperatures and intense physical demands that can quickly lead to heat exhaustion, organ damage, or fatality. Our system integrates continuous skin temperature monitoring, heart rate sensing, microcontroller-based signal processing, and Bluetooth communication to provide real-time physiological data to a mobile application. When predefined safety thresholds are exceeded, the system generates escalating alerts to notify handlers immediately. Lightweight, waterproof, and harness-mounted, the device is built for field durability while maintaining comfort and mobility for the dog. By enabling proactive monitoring rather than reactive intervention, Howler Technology aims to improve animal welfare, reduce preventable injuries, protect valuable operational assets, and enhance mission flexibility in demanding environments.
Students: Brendan McPartlin, Blake Smith, Tristan Eaton, Sumiran Marsani
Advisors: Kovi Bessoff, MD, PhD (Renown), Jared Worchel, DO (Renown)
SafeStep is a pressure-sensor-based smart walker designed to provide objective balance and stability data to support hospital discharge decisions and ongoing at-home monitoring. Current discharge mobility assessments are often subjective and time-consuming, allowing instability to go unnoticed until after patients return home. One in four Americans aged 65 or older falls each year, contributing to injuries, costly readmissions, and billions of dollars in annual healthcare expenses. SafeStep integrates pressure sensors into a familiar assistive device to quantify real-time stability during discharge evaluations. By measuring weight distribution and balance patterns, the system provides clinicians with objective metrics to better assess fall risk and make informed discharge decisions. The broader clinical impact includes reducing post-discharge falls, lowering readmission rates, improving patient safety, and decreasing financial strain on healthcare systems through more informed and data-driven discharge decisions. Key deliverables include an integrated smart walker prototype, embedded firmware for real-time data acquisition and processing, stability assessment logic, and an LCD-based feedback interface. Supporting deliverables include sensor calibration procedures, validation testing results, and complete technical documentation.
Students: Robin Jessee, Alex Reuter, Ben Carrico
MicroSentinel is a proof-of-concept engineering system designed to enhance how small-volume biological samples are monitored. Current microdialysis workflows collect fluid samples for later laboratory analysis, but they do not provide continuous, real-time feedback during sampling. Our team is developing a compact, modular device that integrates directly into the fluid outflow pathway and measures changes in electrical capacitance as the fluid composition varies. The system combines a 3D-printed microfluidic chip with embedded conductive probes, an Arduino-based signal acquisition circuit, and a software interface for real-time visualization and data logging. Operating at clinically relevant flow rates, the prototype demonstrates stable multi-hour performance and reproducible response to controlled chemical perturbations. Rather than replacing laboratory analysis, MicroSentinel augments existing workflows by adding continuous digital trend monitoring without consuming the sample. This approach may expand the functional capabilities of microdialysis systems and provides a scalable foundation for future development in real-time chemical monitoring technologies.
