AR modeling of heart rate signals

Jagadìsh Nayak, P. Subbanna Bhat, Acharya U. Rajendra, U. C. Niranjan, Ong Wai Sing

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

The 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.

Original languageEnglish
Article number1414622
Pages (from-to)422-426
Number of pages5
JournalIEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume2004-January
DOIs
Publication statusPublished - 01-01-2004
Externally publishedYes
EventIEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering - Chiang Mai, Thailand
Duration: 21-11-200424-11-2004

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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