Dr. Changzhi Li, assistant professor of electrical and computer engineering, has received a $400,000 Faculty Early Career Development (CAREER) Award from the National Science Foundation for his proposal, "CAREER: Smart Radar Sensor for Pervasive Motion-Adaptive Health Applications."
Using microwave Doppler radar phase modulation, scientists and healthcare providers have developed new advances in tracking a patient's physiological motions, such as respiration and heartbeat. When implemented, these advances can be monitored remotely by healthcare providers without anything attached to a patient. This technology is ideal for health monitoring over extended periods of time because it does not confine or inhibit a patient and it does not cause discomfort or skin irritation (unlike other devices, such electrodes and straps). Additionally, it may achieve what other devices cannot through fast and remote identification of vital signs in patients. In this way, the technology could be used in remote diagnosis, search and rescue of victims after a natural disaster, or even remote monitoring and surveillance. Recent integration of this technology with radiation oncology imaging processing by Li has offered a very promising solution in tracking mobile tumors in lung cancer patient during radiotherapy.
While this technology predicts an attractive way to replace commonly prescribed chest-strap or fingertip monitors, it has some critical limitations. Because physiological motion is very weak compared to possible random body motion and sensor shaking, the noise caused by random body motion may easily overwhelm the physiological signals that are monitored through this technology. Although speed and frequency of physiological movements can be detected, up to this point it has been difficult to reliably uncover the original movement pattern — which has much more health and scientific importance than simply the rates of respiration and heartbeat. Additionally, sufficient work has not been done in the past to address the issues of integrating the system into a low-cost small chip, package, or module, so that it can reach out to the daily routine of ordinary people.
Li's group in the Department of Electrical and Computer Engineering at Texas Tech aims to resolve these problems by using novel adaptive circuits and sensor fusion. A 'smart' portable biomedical radar sensor will be devised for pervasive motion-adaptive healthcare based on a hybrid of radar and camera solutions. Agile RF/analog circuits and demodulation algorithms will be developed to realize software configuration to sensor hardware. Furthermore, a CMOS radar-on-chip solution will be conceived to demonstrate the feasibility of truly portable biomedical radar devices that could be as easy to use as an iPhone.
If successful, this research can be directly used for the monitoring and treatment of sleep apnea and sudden infant death syndrome. When configured as a nonlinear vibrometer, the radar will also advance approaches to monitoring rotating and reciprocating machinery in the transportation and manufacturing industries. Li's research will provide a thorough understanding of the capability and limitations of continuous wave radar sensors for short-range applications. The studies are at the crossroads of engineering and healthcare disciplines, and will enable unique educational opportunities in engineering curriculum.
This project will benefit from collaboration with National Instruments on both research and education.