A MULTIVARIATE STATISTICAL ANALYSIS OF MUSCULAR BIOPOTENTIAL FOR HUMAN ARM MOVEMENT CHARACTERIZATION

Giuliano Alves da Silva, Maria Cláudia Ferrari de Castro, Carlos Eduardo Thomaz

Abstract

Pattern recognition of electromyographic signals consists of a hard task due to the high dimensionality of the data and noise presence on the acquired signals. This work intends to study the data set as a multivariate pattern recognition problem by applying linear transformations to reduce the data dimensionality. Five volunteers contributed in a previous experiment that acquired the myoelectrical signals using surface electrodes. Attempts to analyse the groups of acquired data by means of descriptive statistics have shown to be inconclusive. This works shows that the use of multivariate statistical techniques such as Principal Components Analysis (PCA) and Maximum uncertainty Linear Discriminant Analysis (MLDA) to characterize the acquired set of signals through low dimensional scatter plots provides a new understanding of the data spread, making easier its analysis. Considering the arm horizontal movement and the acquired set of data used in this research, a multivariate linear separation between the patterns of interest quantified by the distance of Bhattacharyya suggests that it’s possible not only to characterize the angular joint position, but also to confirm that different movements recruit similar amounts of energy to be executed.

References

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Paper Citation


in Harvard Style

Silva G., Castro M. and Thomaz C. (2009). A MULTIVARIATE STATISTICAL ANALYSIS OF MUSCULAR BIOPOTENTIAL FOR HUMAN ARM MOVEMENT CHARACTERIZATION . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 227-232. DOI: 10.5220/0001433802270232


in Bibtex Style

@conference{biosignals09,
author={Giuliano Alves da Silva and Maria Cláudia Ferrari de Castro and Carlos Eduardo Thomaz},
title={A MULTIVARIATE STATISTICAL ANALYSIS OF MUSCULAR BIOPOTENTIAL FOR HUMAN ARM MOVEMENT CHARACTERIZATION},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={227-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001433802270232},
isbn={978-989-8111-65-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
TI - A MULTIVARIATE STATISTICAL ANALYSIS OF MUSCULAR BIOPOTENTIAL FOR HUMAN ARM MOVEMENT CHARACTERIZATION
SN - 978-989-8111-65-4
AU - Silva G.
AU - Castro M.
AU - Thomaz C.
PY - 2009
SP - 227
EP - 232
DO - 10.5220/0001433802270232