A5083478640- Non-Invasive Vital Sign Monitoring
- Hemodynamic Monitoring and Therapy
- Heart Rate Variability and Autonomic Control
University of Florida
2018-2019
Institute For Defense Analyses
2019
The advancement of vital sign radar technology has proven to be a useful tool in assessing various physiological dynamics, including heartbeat and respiration. There remains several signal processing challenges this field, which include overcoming the nonlinearities harmonics that populate power spectrum. Respiration distort overwhelm measurement due large amplitude. A supervised machine learning algorithm, gamma filter, offers an efficient, calibration-free solution model time series given...
Vital signs radar has proven to be an interesting and useful tool; however it is still limited by a few key problems. One of these the generation harmonics due nonlinearities arising from large signal amplitude respiration when compared that heartbeat. As result, arise in spectrum which confound accurate measurement either. The gamma filter supervised machine learning based approach offers calibration-free computationally efficient solution for many nonlinear filtering applications. Here,...