CNS Core: Small: Non-contact Monitoring of Respiration and Heart Rates Through Light-wave Sensing

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In many health care settings there is a need to discreetly monitor respiration and heart rates in humans. The applications for monitoring include warning fatigued drivers or pilots, active feedback for virtual reality or gaming, anxiety monitoring, security screening, and health monitoring for sleep apnea, tachypnea, tachycardia, and bradycardia. This project investigates a discreet, non-contact method of using light to monitor respiration and heart rates. In concept, the intensity of light reflected from a subject follows the subtle body movements associated with breathing and heartbeat, enabling extraction of the rates. The method offers high privacy with zero risks of radio interference, but its theoretical effectiveness and accuracy are not yet clear. This project seeks to understand the fundamental limits of the technique, which will determine how well it can perform in real-world situations. Apart from the technological interest, the project will enable unique educational opportunities for next-generation engineers and scientists, including class modules as well as training and outreach. This work will use an outreach effort with light sensing and communication kits in which students, through programs like OSU Summer Bridge or Discovery Days, build their own low-cost, portable, light-based wireless communication system, a highly successful activity for stimulating interest and recruitment. The PIs will continue their commitment to mentoring underrepresented students through the OK Louis Stokes Alliance for Minority Participation program. The goal of the work is to determine the limits of lightwave respiration and heartrate monitoring as a function of source intensity, wavelength, ambient lighting, photodetector, range, clothing, and optical layout. A human-like robot will be built and covered with artificial skin and multiple clothing items. Using actuators controlled by a microcontroller, it will accurately simulate motions produced by humans during breathing. Different lighting conditions, sources, optical layouts and fields of view, clothing types, subject positions/orientations, and actuator patterns will be systematically measured in controlled conditions to determine the effects on the system signal-to-noise ratio. Signal processing algorithms will be applied to measured data to test the statistical accuracy and to determine how well rates can be extracted from noisy ambient conditions. The resulting data will provide a foundation upon which theoretical models of the sensor performance can be developed. Importantly, it will also reveal important science about the limitations of information content that can be conveyed through simple scattering and intensity measurements with modern photodetector technology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.