ABSTRACT

Sleep disordered breathing (SDB) in children is considered to be a public health problem with serious consequences such as decreased cognitive function, poor school performance, daytime sleepiness and increased cardiovascular risk. Current diagnosis of SDB is performed in hospital sleep laboratories by monitoring patients with a host of cardiorespiratory sensors attached at various positions on the patient?s body. This obtrusive form of monitoring is inconvenient to patients and require tremendous amount of attention from technicians to ensure study quality. Children, especially, tolerate the study very poorly; often removing sensors, having trouble sleeping, and necessitating repeat investigations. This project aims to develop a new method to remotely and continuously monitor breathing volume and breathing patterns of human subjects during sleep studies using optical signals assisted by radio frequency signals. We introduce RadiOptiMeter, a hybrid radio-optical breath volume monitoring approach that couple the unique characteristics of radio frequency (RF) signals with image stream captured by a depth-CO2-thermal camera to accurately estimate breathing volume of sleeping patients from afar. This study is the first step in the development of non-invasive respiratory monitoring. Utilizing this novel and non-invasive device to measure breathing during sleep will begin a research program to promote future diagnosis of SDB in the comfort of the child?s home, with no in-hospital laboratory expenses or the expense of the disposable medical equipment which equates to thousands of dollars a year in each sleep laboratory.

This project will investigate a new method to continuously monitor breathing volume and breathing patterns of humans during in-hospital sleep studies using radio frequency and optical signals. We introduce RadiOptiMeter, a hybrid radio-optical breath volume monitoring approach that couple the unique characteristics of radio frequency (RF) signals with image stream captured by a depth-CO2-thermal camera to accurately and continuously estimate breathing volume of sleeping patients from afar. We propose techniques to address challenges brought about by the body movement during sleep, environmental wireless signal noises, and the diversity of patient populations. An expected outcome is a robust and accurate breathing volume monitoring system for SDB studies. The cooperation between each of the proposed devices allows us to exploit the synergistic effects of the devices to cover the limitations imposed by each device type and provides system redundancies. These redundancies ensure reliability for long-term monitoring tasks, which are critical for clinical applications. Our proposed research will make the following key contributions to enable new non-contact vital signal monitoring system: (1) Analytical models, experimental tools, and evaluation results of a breathing volume estimation method using a vision-based system (VVE) which include 4D volumetric model and skeletal structure analysis from depth- CO2-thermal (DCT) camera outputs. (2) Analytical models, experimental hardware and software components, and evaluation results of a RF-based breathing volume estimation (RVE) system, that uses neural-network-based machine learning for chest displacement- to-volume matching. (3) A hybrid radio-optical breathing volume estimation system (RadiOptiMeter) that synergistically combines the VVE and RVE to perform continuous and fine-grain monitoring. RadiOptiMeter includes body movement tracking, automatic antenna steering, and a set of controlling and synchronizing algorithms for a harmonic integration of the whole system. This collaborative effort between researchers at the Department of Computer Science and Engineering and medical doctors at Sleep Medicine Research at the Children?s Hospital Colorado is the first step in the development of non-invasive respiratory monitoring. A novel non-invasive device to measure breathing during sleep will be the first step in the necessary foundational research to promote future diagnosis of SDB in the comfort of the child?s home, with no in-hospital laboratory expenses or the expense of the disposable medical equipment which equates to thousands of dollars a year in each sleep laboratory. This project also provides an excellent methodd to train graduate students to conduct this vision-based research project. The RadiOptiMeter concepts serves as an exciting and appealing tool for structuring a variety of educational activities. Moreover, the project results will be disseminated through scholarly publications and active outreach through our existing and potential industrial partners.

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