Low complexity tracking for long term monitoring of heart sounds

This paper describes a novel framework for tracking heart sounds. For a given heart sound component (e.g. S1) candidate features (e.g. peaks) are mapped to states and assigned appropriate local scores. A low complexity dynamic programming based algorithm is developed to select the largest most consi...

Full description

Saved in:
Bibliographic Details
Published in:2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2008-01, p.17-20
Main Authors: Patangay, Abhilash, Tewfik, Ahmed
Format: Article
Language:English
Subjects:
Complexity theory
Dynamic programming
Feature extraction
Heart
Heuristic algorithms
Measurement
Monitoring
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper describes a novel framework for tracking heart sounds. For a given heart sound component (e.g. S1) candidate features (e.g. peaks) are mapped to states and assigned appropriate local scores. A low complexity dynamic programming based algorithm is developed to select the largest most consistent feature from the candidate features. This algorithm is also capable of detecting multiple simultaneous features for improved noise immunity. The proposed algorithm has linear complexity with time and cubic complexity with the number of features to be tracked. Data from six swine balloon-occlusion studies are used for preliminary testing of the algorithm. The S1 amplitude and heart sound ejection time (HSET) are found to be statistically significantly correlated with changes in systolic performance due to ischemia induction.
ISSN:1094-687X
1558-4615
DOI:10.1109/IEMBS.2008.4649080