Title :
Adaptive mean and trend removal of heart rate variability using Kalman filtering
Author :
Schlogl, A. ; Fortin, J. ; Habenbacher, W. ; Akay, M.
Author_Institution :
Inst. of Biomed. Eng., Graz Univ. of Technol., Austria
Abstract :
Analysis of heart rate variability requires the calculation of the mean heart rate. Adaptive methods are important for online and real-time parameter estimation. In this paper, we demonstrate the use of Kalman filtering to estimate adaptively the mean heart rate and remove the trend.
Keywords :
adaptive Kalman filters; adaptive signal processing; electrocardiography; medical signal processing; parameter estimation; spectral analysis; ECG processing; Kalman filtering; QRS detection; R-to-R intervals; adaptive mean; computational efficiency improvement; electrodiagnostics; heart rate variability; online real-time parameter estimation; spectrum estimation; trend removal; Adaptive filters; Biomedical engineering; Equations; Error correction; Filtering; Heart rate; Heart rate variability; Kalman filters; State estimation; State-space methods;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1018997
