The design of a robust and intelligent phased array Non-Contact Vital Signs (NCVS) sensor system

For the past few years, it has been the desire of the healthcare industry to have a non-invasive system capable of continuous, accurate, and long-term monitoring of human vital signs. Having a system that can measure and record vital signs, such as heart rates and respiration rates, is an invaluable tool for physicians who need to make rapid life-and-death decisions. Such a system would also be an effective tool to help physicians make better informed decisions when viewing a patient’s long-term monitored data. Therefore, there has been a large increase in research activities to develop a system that can monitor a patient’s vital signs and quickly transmit the information to healthcare professionals. Non-contact vital signs (NCVS) monitoring system are particularly attractive for long term vital signs monitoring because there are no wires, electrodes, wearable devices, nor contact-based sensors for the subjects to worry about.
In this thesis we will investigate improvements made to an existing Doppler-based non-contact vital signs (NCVS) biosensor we have built in Professor Donald Y. C. Lie’s RF/Analog SoC Lab. The main focus of this thesis will be on improving the effective range of the system and the creation of a “smart” system capable of detecting a patient’s location and movement. To determine the accuracy of the NCVS sensor, the heart rate measurements from the system are compared against an external contact-based piezoelectric finger sensor as a reference. In previous works, the NCVS sensor performance was tested within a clutter-free anechoic chamber inside Dr. Lie’s RF/Analog SoC Lab. In this work, to examine the performance of the NCVS sensor in a more practical setting, all tests were performed within the typical Herman-Miller type office cubicle setting, inside a section of the RF/Analog SoC Lab. Additionally, I will detail the 5th and 6th generation revisions and improvement to the NCVS sensor.

This thesis won 1st Place in the Texas Tech University Outstanding Thesis and Dissertation Award, Mathematics, Physical Sciences & Engineering, 2016.

Embargo status: Restricted from online display. To request an access exception from the author, click on the PDF link to the left.