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: Nemati, Shamim, Malhotra, Atul, Clifford, Gari D.
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Hindawi Pub. Corp/Springer 2011
Online Access:http://hdl.handle.net/1721.1/67021

Internet

http://hdl.handle.net/1721.1/67021

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