Title :
ML Period Estimation With Application to Vital Sign Monitoring
Author :
Conte, Ermanna ; Filippi, Alessio ; Tomasin, Stefano
Author_Institution :
Univ. of Padova, Padova, Italy
Abstract :
The real time estimation of the period of signals that are periodic over short time intervals requires fast algorithms. In this letter, the maximum likelihood (ML) period estimator is derived for a periodic signal with additive white Gaussian noise. A low complexity approximation is then proposed, and compared with the state of the art of the estimation techniques in a practical scenario for the remote estimation of human heart rate using an ultra wide band radar.
Keywords :
AWGN; maximum likelihood estimation; medical signal processing; ML period estimation; additive white Gaussian noise; human heart rate; remote estimation; ultrawideband radar; vital sign monitoring; Complexity theory; Correlation; Heart rate; Maximum likelihood estimation; Noise; Radar; Bioinformatics; biomedical signal processing; estimation and classification theory and methods; including genomics; statistical signal processing;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2010.2071382
