Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNayak, J.
dc.contributor.authorBhat, P.S.
dc.contributor.authorRajendra, A.U.
dc.contributor.authorNiranjan, U.C.
dc.contributor.authorSing, O.W.
dc.identifier.citationIEEE Region 10 Annual International Conference, Proceedings/TENCON, 2004, Vol.2004-January, , pp.422-426en_US
dc.description.abstractThe electrocardiogram (ECG) is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks etc may contain useful information about the nature of disease afflicting the heart. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the heart rate variability signal is used as the base signal for the highly useful in diagnostics. This paper deals with the analysis of eight cardiac abnormalities using Auto Regressive (AR), modeling technique. The results are tabulated below for specific example. � 2004 IEEE.en_US
dc.titleAR modeling of heart rate signalsen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.