Assessing Sample Entropy of physiological signals by the norm component matrix algorithm: Application on muscular signals during isometric contraction

Paolo Castiglioni, Sebastian Zurek, Jaroslaw Piskorski, Marcin Kosmider, Przemyslaw Guzik, Emiliano Ce, Susanna Rampichini, Giampiero Merati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sample Entropy (SampEn) is a popular method for assessing the unpredictability of biological signals. Its calculation requires to preliminarily set the tolerance threshold r and the embedding dimension m. Even if most studies select m=2 and r=0.2 times the signal standard deviation, this choice is somewhat arbitrary. Effects of different r and m values on SampEn have been rarely assessed, because of the high computational burden of this task. Recently, however, a fast algorithm for estimating correlation sums (Norm Component Matrix, NCM) has been proposed that allows calculating SampEn quickly over wide ranges of r and m.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages5053-5056
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Fingerprint Dive into the research topics of 'Assessing Sample Entropy of physiological signals by the norm component matrix algorithm: Application on muscular signals during isometric contraction'. Together they form a unique fingerprint.

  • Cite this

    Castiglioni, P., Zurek, S., Piskorski, J., Kosmider, M., Guzik, P., Ce, E., Rampichini, S., & Merati, G. (2013). Assessing Sample Entropy of physiological signals by the norm component matrix algorithm: Application on muscular signals during isometric contraction. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 5053-5056). [6610684] https://doi.org/10.1109/EMBC.2013.6610684