UNVEILING INTRINSIC SIMILARITY - Application to Temporal Analysis of ECG

André Lourenço, Ana Fred

2008

Abstract

The representation of data in some visual form is one of the first steps in a data-mining process in order to gain some insight about its structure. We propose to explore well known visualization and unsupervised learning techniques, namely clustering, to improve the understanding about the data and to enhance possible relations or intrinsic similarity between patterns. Specifically, Clustering Ensemble Methods are exploited separately and combined to provide a clearer visualization of data organization. The presented methodology is used to improve the understanding of ECG signal acquired during Human Computer Interaction (HCI).

Paper Citation

in Harvard Style

Lourenço A. and Fred A. (2008). UNVEILING INTRINSIC SIMILARITY - Application to Temporal Analysis of ECG . In Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008) ISBN 978-989-8111-18-0, pages 104-109. DOI: 10.5220/0001070201040109

in Bibtex Style

@conference{biosignals08,
author={André Lourenço and Ana Fred},
title={UNVEILING INTRINSIC SIMILARITY - Application to Temporal Analysis of ECG},
booktitle={Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008)},
year={2008},
pages={104-109},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001070201040109},
isbn={978-989-8111-18-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bio-inspired Systems and Signal Processing - Volume 2: BIOSIGNALS, (BIOSTEC 2008)
TI - UNVEILING INTRINSIC SIMILARITY - Application to Temporal Analysis of ECG
SN - 978-989-8111-18-0
AU - Lourenço A.
AU - Fred A.
PY - 2008
SP - 104
EP - 109
DO - 10.5220/0001070201040109