Data Fusion for Improved Respiration Rate Estimation

Data Fusion for Improved Respiration Rate Estimation

We present an application of a modified Kalman-Filter (KF) framework for data fusion to the estimation of respiratory rate from multiple physiological sources which is robust to background noise. A novel index of the underlying signal quality of respiratory signals is presented and then used to modi...

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Bibliographic Details
Main Authors:	Gari D. Clifford, Atul Malhotra, Shamim Nemati
Format:	Article
Language:	English
Published:	SpringerOpen 2010-01-01
Series:	EURASIP Journal on Advances in Signal Processing
Online Access:	http://dx.doi.org/10.1155/2010/926305

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