Imperial College London
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ProfessorDarioFarina

Faculty of Engineering, Department of Bioengineering

Chair in Neurorehabilitation Engineering
 
 
 
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Contact

 

+44 (0)20 7594 1387d.farina Website

 
 
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Location

 

RSM 4.15Royal School of MinesSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{OKeeffe:2022:10.1101/2022.11.02.514949,
author = {OKeeffe, R and Shirazi, SY and Del, Vecchio A and Ibáñez, J and Mrachacz-Kersting, N and Bighamian, R and Rizzo, J and Farina, D and Atashzar, SF},
doi = {10.1101/2022.11.02.514949},
title = {Low-frequency motor cortex EEG predicts four levels of rate of change of force during ankle dorsiflexion},
url = {http://dx.doi.org/10.1101/2022.11.02.514949},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <jats:title>Abstract</jats:title><jats:p>The movement-related cortical potential (MRCP) is a low-frequency component of the electroencephalography (EEG) signal recorded from the motor cortex and its neighboring cortical areas. Since the MRCP encodes motor intention and execution, it may be utilized as an interface between patients and neurorehabilitation technologies. This study investigates the EEG signal recorded from the Cz electrode to discriminate between four levels of rate of force development (RFD) of the tibialis anterior muscle. For classification, three feature sets were evaluated to describe the EEG traces. These were (i)<jats:italic>MRCP morphological characteristics</jats:italic>in the<jats:italic>δ</jats:italic>-band such as amplitude and timing, (ii)<jats:italic>MRCP statistical characteristics</jats:italic>in the<jats:italic>δ</jats:italic>-band such as mean, standard deviation, and kurtosis, and (iii)<jats:italic>wideband time-frequency features</jats:italic>in the 0.5-90 Hz range. Using a support vector machine for classification, the four levels of RFD were classified with a mean (SD) accuracy of 82% (7%) accuracy when using the time-frequency feature space, and with an accuracy of 75% (12%) when using the MRCP statistical characteristics. It was also observed that some of the key features from the statistical and morphological sets responded monotonically to the intensity of the RFD. Examples are slope and standard deviation in the (0, 1)s window for the statistical, and<jats:italic>min</jats:italic><jats:sub>1</jats:sub>and<jats:italic>min<jats:sub>n</jats:sub></jats:italic>for the morphological sets. This monotonical response of features explains the observed performance of the<jats:italic>δ</jats:italic>-band MRCP and corresponding high discriminative power. Results from temporal analysis
AU  - OKeeffe,R
AU  - Shirazi,SY
AU  - Del,Vecchio A
AU  - Ibáñez,J
AU  - Mrachacz-Kersting,N
AU  - Bighamian,R
AU  - Rizzo,J
AU  - Farina,D
AU  - Atashzar,SF
DO  - 10.1101/2022.11.02.514949
PY  - 2022///
TI  - Low-frequency motor cortex EEG predicts four levels of rate of change of force during ankle dorsiflexion
UR  - http://dx.doi.org/10.1101/2022.11.02.514949
ER  -
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