Driving Health Intelligence: Eye-Tracking for Early Disease Detection in Automobiles
Modern vehicles are evolving into intelligent health platforms, integrating eye-tracking systems capable of capturing high-frequency visual data with exceptional spatial precision. This presentation explores how advanced driver monitoring systems leverage high-resolution oculomotor data to detect early biomarkers of neurological and metabolic disorders during routine driving. Subtle changes in saccadic velocity, fixation stability, and pupillary reflex can signal the onset of neurological conditions well before conventional clinical diagnosis, enabling earlier intervention and improved long-term outcomes.
For diabetes management, continuous ocular monitoring offers a non-invasive method to detect hypoglycemic episodes in real time. Variations in pupil dilation and blink frequency have been correlated with acute glycemic fluctuations, enabling predictive alerts that can reduce diabetes-related driving risks. Beyond metabolic and neurological conditions, eye-tracking metrics quantify cognitive load, fatigue, and mental health indicators with strong diagnostic reliability when analyzed using advanced machine learning models trained on multi-parameter behavioral datasets. However, deploying health surveillance systems in vehicles that continuously process large volumes of biometric data raises critical concerns. Issues of data privacy, cybersecurity resilience, consent frameworks, and regulatory fragmentation remain significant barriers to widespread adoption.
This session presents data-driven insights, system architecture considerations, and ethical guardrails for transforming automobiles into proactive health intelligence hubs, shifting vehicles from passive transport systems to real-time, preventive healthcare ecosystems.
About the speaker
Thangeswaran Natarajan
Senior Manager, Software Engineer at General Motors
Thangeswaran Natarajan is a seasoned Technology Leader and Senior Software Engineering Manager with over 20 years of experience in embedded systems development across medical devices and autonomous automotive platforms. He has led global engineering teams for more than 14 years, successfully delivering complex, safety-critical products from concept through regulatory approval and commercialization. Thangesh currently serves as Senior Software Engineering Manager at General Motors, leading teams focused on ASIL-D functional safety systems, SafeRTOS-based safety islands, and high-performance Linux platforms supporting infotainment and cloud applications. Previously at Rivian, he led a 40+ member engineering organization delivering embedded software for self-driving systems across the R1T, R1S, and Amazon EDV platforms. His expertise spans ADAS SoCs, secure bootloaders, OTA updates, middleware development, cybersecurity, and hardware abstraction layers. In the medical device domain, Thangesh played a key leadership role at Stryker and Physio-Control in developing next-generation defibrillators and other life-critical systems. He has successfully delivered eight FDA (510k and PMA) and CE-certified medical products with zero field-related software failures in key programs. He is also a co-inventor on U.S. patent applications related to enhanced defibrillation technologies. Thangesh holds an MBA from the University of Washington (3.81 GPA), an MS in Software Engineering from BITS Pilani, and a BE in Electronics and Communication Engineering. He is PMP and PMI-ACP certified, Six Sigma Green Belt trained, and skilled in Linux, QNX, SafeRTOS, embedded C/C++, and safety-critical architecture. He is recognized for building high-performing teams, driving innovation, and delivering mission-critical systems with excellence.