Convolutional neural network proposal for wrist position classification from electromyography signals

Alvaro D. Orjuela-Canon; Oscar J. Perdomo-Charry; Cesar H. Valencia-Nino; Leonardo Forero

doi:10.1109/ColCACI50549.2020.9247924

Convolutional neural network proposal for wrist position classification from electromyography signals

Alvaro D. Orjuela-Canon
, Oscar J. Perdomo-Charry
, Cesar H. Valencia-Nino
, Leonardo Forero

Research output: Chapter in Book/Inform › Chapter › Research

Abstract

Commonly, electromyography (EMG) signals have been employed for movements or pattern classification. For this, different digital signals processing methods are applied to extract features, before a classification stage. The present work deals with a proposal based on the use of image classification employing deep learning techniques. The images were obtained from a spectrogram analysis as a previous process of the convolutional neural network employment. Then, a classification of five positions from wrist movements is carried out the model. Results showed that the accuracy is comparable to similar techniques employed with a shallow neural network and a deep neural network applied to the same dataset.

Translated title of the contribution	Propuesta de red neuronal convolucional para la clasificación de la posición de la muñeca a partir de señales electromiográficas
Original language	English (US)
Title of host publication	2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings
Editors	Alvaro David Orjuela-Canon
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728194066
DOIs	https://doi.org/10.1109/ColCACI50549.2020.9247924
State	Published - Aug 7 2020
Event	2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Virtual, Cali, Colombia Duration: Aug 7 2020 → Aug 9 2020

Publication series

Name	2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings

Conference

Conference	2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020
Country/Territory	Colombia
City	Virtual, Cali
Period	8/7/20 → 8/9/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Decision Sciences (miscellaneous)
Information Systems and Management
Control and Optimization

Access to Document

10.1109/ColCACI50549.2020.9247924

Cite this

Orjuela-Canon, A. D., Perdomo-Charry, O. J., Valencia-Nino, C. H., & Forero, L. (2020). Convolutional neural network proposal for wrist position classification from electromyography signals. In A. D. Orjuela-Canon (Ed.), 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings Article 9247924 (2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ColCACI50549.2020.9247924

Orjuela-Canon, Alvaro D. ; Perdomo-Charry, Oscar J. ; Valencia-Nino, Cesar H. et al. / Convolutional neural network proposal for wrist position classification from electromyography signals. 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings. editor / Alvaro David Orjuela-Canon. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings).

@inbook{f97ecf2dacc14b25a422d4330118c678,

title = "Convolutional neural network proposal for wrist position classification from electromyography signals",

abstract = "Commonly, electromyography (EMG) signals have been employed for movements or pattern classification. For this, different digital signals processing methods are applied to extract features, before a classification stage. The present work deals with a proposal based on the use of image classification employing deep learning techniques. The images were obtained from a spectrogram analysis as a previous process of the convolutional neural network employment. Then, a classification of five positions from wrist movements is carried out the model. Results showed that the accuracy is comparable to similar techniques employed with a shallow neural network and a deep neural network applied to the same dataset. ",

author = "Orjuela-Canon, \{Alvaro D.\} and Perdomo-Charry, \{Oscar J.\} and Valencia-Nino, \{Cesar H.\} and Leonardo Forero",

note = "Funding Information: The authors thank to Universidad el Rosario, Universidad Santo Tomas and Universidade Estadual do Rio de Janeiro for the support in this work. In addition, special thanks to professor Andres Ruiz in Universidad Antonio Nari?o for his support in the acquisition signals employed to develop the present proposal. Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 ; Conference date: 07-08-2020 Through 09-08-2020",

year = "2020",

month = aug,

day = "7",

doi = "10.1109/ColCACI50549.2020.9247924",

language = "English (US)",

series = "2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Orjuela-Canon, \{Alvaro David\}",

booktitle = "2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings",

address = "United States",

}

Orjuela-Canon, AD, Perdomo-Charry, OJ, Valencia-Nino, CH & Forero, L 2020, Convolutional neural network proposal for wrist position classification from electromyography signals. in AD Orjuela-Canon (ed.), 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings., 9247924, 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020, Virtual, Cali, Colombia, 8/7/20. https://doi.org/10.1109/ColCACI50549.2020.9247924

Convolutional neural network proposal for wrist position classification from electromyography signals. / Orjuela-Canon, Alvaro D.; Perdomo-Charry, Oscar J.; Valencia-Nino, Cesar H. et al.
2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings. ed. / Alvaro David Orjuela-Canon. Institute of Electrical and Electronics Engineers Inc., 2020. 9247924 (2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings).

Research output: Chapter in Book/Inform › Chapter › Research

TY - CHAP

T1 - Convolutional neural network proposal for wrist position classification from electromyography signals

AU - Orjuela-Canon, Alvaro D.

AU - Perdomo-Charry, Oscar J.

AU - Valencia-Nino, Cesar H.

AU - Forero, Leonardo

N1 - Funding Information: The authors thank to Universidad el Rosario, Universidad Santo Tomas and Universidade Estadual do Rio de Janeiro for the support in this work. In addition, special thanks to professor Andres Ruiz in Universidad Antonio Nari?o for his support in the acquisition signals employed to develop the present proposal. Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/8/7

Y1 - 2020/8/7

N2 - Commonly, electromyography (EMG) signals have been employed for movements or pattern classification. For this, different digital signals processing methods are applied to extract features, before a classification stage. The present work deals with a proposal based on the use of image classification employing deep learning techniques. The images were obtained from a spectrogram analysis as a previous process of the convolutional neural network employment. Then, a classification of five positions from wrist movements is carried out the model. Results showed that the accuracy is comparable to similar techniques employed with a shallow neural network and a deep neural network applied to the same dataset.

AB - Commonly, electromyography (EMG) signals have been employed for movements or pattern classification. For this, different digital signals processing methods are applied to extract features, before a classification stage. The present work deals with a proposal based on the use of image classification employing deep learning techniques. The images were obtained from a spectrogram analysis as a previous process of the convolutional neural network employment. Then, a classification of five positions from wrist movements is carried out the model. Results showed that the accuracy is comparable to similar techniques employed with a shallow neural network and a deep neural network applied to the same dataset.

UR - https://www.scopus.com/pages/publications/85097551739

UR - https://www.scopus.com/pages/publications/85097551739#tab=citedBy

U2 - 10.1109/ColCACI50549.2020.9247924

DO - 10.1109/ColCACI50549.2020.9247924

M3 - Chapter

AN - SCOPUS:85097551739

T3 - 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings

BT - 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings

A2 - Orjuela-Canon, Alvaro David

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020

Y2 - 7 August 2020 through 9 August 2020

ER -

Orjuela-Canon AD, Perdomo-Charry OJ, Valencia-Nino CH, Forero L. Convolutional neural network proposal for wrist position classification from electromyography signals. In Orjuela-Canon AD, editor, 2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9247924. (2020 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2020 - Proceedings). doi: 10.1109/ColCACI50549.2020.9247924

Convolutional neural network proposal for wrist position classification from electromyography signals

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this