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Authors: Eleonora Sulas ; Luigi Raffo ; Marco Monticone and Danilo Pani

Affiliation: University of Cagliari, Italy

ISBN: 978-989-758-279-0

Keyword(s): Scoliosis, EMG, Adaptive Filters, RLS, ECG.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: Adolescent idiopathic scoliosis is defined as a three-dimensional deformity of the spine and trunk occurring in about 2.5% of most populations. It is usually analyzed radiographically, but electromyography (EMG) can be also used, since muscles activity is correlated to deformity progression. EMG ratio is a numerical index used in the literature to provide information about scoliosis progression. Trunk EMG recordings are strongly affected by the electrocardiogram (ECG) of the subject. Previous studies removed this interference from the EMG signal by blanking the QRS complexes of the ECG but, as a consequence, several segments of the signal are removed. Furthermore, the other relevant ECG waves such as P and T are not cancelled and can invalidate the computation of parameters such as the EMG ratio. The aim of this study is to evaluate the possibility, by means of a modified recording protocol including further electrodes, to completely remove the ECG interference by adopting a multi-ref erence recursive least square (RLS) adaptive filter. The results of the study reveal how the complete clearing of the ECG from the EMG channels leads to different numerical values of the index, compared to the QRS blanking, more reliable and meaningful for the clinicians. (More)

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Paper citation in several formats:
Sulas E., Raffo L., Monticone M. and Pani D. (2018). Adaptive Filtering for Electromyographic Signal Processing in Scoliosis Indexes Estimation.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS, ISBN 978-989-758-279-0, pages 161-167. DOI: 10.5220/0006586001610167

@conference{biosignals18,
author={Eleonora Sulas and Luigi Raffo and Marco Monticone and Danilo Pani},
title={Adaptive Filtering for Electromyographic Signal Processing in Scoliosis Indexes Estimation},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,},
year={2018},
pages={161-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006586001610167},
isbn={978-989-758-279-0},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOSIGNALS,
TI - Adaptive Filtering for Electromyographic Signal Processing in Scoliosis Indexes Estimation
SN - 978-989-758-279-0
AU - Sulas E.
AU - Raffo L.
AU - Monticone M.
AU - Pani D.
PY - 2018
SP - 161
EP - 167
DO - 10.5220/0006586001610167

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