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K-NN Based Interpolation to Handle Artifacts for Heart Rate Variability Analysis

Authors:

Shahina Begum, Mohd. Siblee Islam , Mobyen Uddin Ahmed, Peter Funk

Research group:

Artificial Intelligence and Intelligent Systems

Publication Type:

Conference/Workshop Paper

Venue:

IEEE International Symposium on Signal Processing and Information Technology

Abstract

Heart rate variability (HRV) is a popular parameter for depicting activities of autonomous nervous system and helps to explain various physiological activities of the body. A small amount of artifacts can produce significant changes especially, for time domain HRV features. Manual correction of artifacts performed by visual inspection of the signal by experts is tedious and time consuming and often leads to incorrect result especially for long term recordings. Therefore, an automatic artifact removing approach that helps to provide clinically useful HRV analysis is valuable. This paper proposes an algorithm that detects and replaces artifacts from inter-beat interval (IBI) signal for HRV analysis. The detection is mainly based on windowing technique and interpolation is performed using the k-nearest neighbour (K-NN) algorithm. The experimental work shows a promising performance in handling artifacts for HRV analysis using electrocardiogram (ECG) sensor signal.

Bibtex

@inproceedings{Begum2213,
author = {Shahina Begum and Mohd. Siblee Islam and Mobyen Uddin Ahmed and Peter Funk},
title = {K-NN Based Interpolation to Handle Artifacts for Heart Rate Variability Analysis},
month = {December},
year = {2011},
booktitle = {IEEE International Symposium on Signal Processing and Information Technology},
url = {http://www.es.mdu.se/publications/2213-}
}