When Used with Noncontact Vital Sign Measurement Radar Apparatus, Algorithm Removes Respiration Distortion for More Accurate Heart Rate Data
This algorithm, developed for noncontact measurement radar monitors, can suppress respiration signals and extract heartbeat pulses to provide faster and more accurate vital signs data. The vital signs monitoring market is expected to reach $4.734 billion by 2018 worldwide. Traditional devices and methods of obtaining noncontact vital signs are performed by either front-side or back-side frequency-domain techniques; however, both methods suffer from respiration wavelength interference and distortion. As a result, the estimations are relatively inaccurate. Alternative methods of obtaining heart rate estimations tend to take a long time, making the methods unfit for real-time applications. Researchers at the University of Florida have developed an algorithm that can extract respiration signals from heartbeat pulses to better estimate vital signs quickly. This time-domain vital sign extraction and estimation can be used in human healthcare, veterinary medicine, and biology research.
This algorithm, used with noncontact vital sign measurement radar, overcomes distortion caused by respiration to gain more accurate heart rate data
- Extracts time-domain waveforms for respiration and heartbeats, eliminating respiration distortion from heartbeat waveform
- Provides real-time respiration and heartbeat data, enabling fast vital sign estimation
- Reflects the instant change of heart rate and respiration rate, allowing for Heart Rate Variability (HRV) analysis
One traditional method of obtaining a remote heart rate involves reading reflected radar signals from the front side of a patient; however, this reading is often distorted due to respiration interference. An alternative to this method is to read from the back side of a patient, requiring a very specific posture for an accurate reading. Advanced signal processing methods need a long period of time to obtain an accurate reading, limiting real-time applications. Therefore, there exists a need for a method of obtaining vital signs quickly and accurately for real-time applications. This algorithm works with a wireless, noncontact vital sign measurement radar, using time-domain techniques, rather than frequency-domain techniques, to remove the distortion caused by respiration interference. The algorithm utilizes radar output signals, which are subtracted from radar baseband signals in the time-domain, in order to estimate vital signs. In contrast to available spectral-domain methods, this algorithm and radar sensor can get accurate heart rate readings in six seconds.