Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization

M. A. Ben Arous; M. Dunbar; S. Arfaoui; A. Mitiche; Y. Ouakrim; A. Fuentes; G. Richardson; N. Mezghani

doi:10.5220/0006586601760181

Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization

M. A. Ben Arous, M. Dunbar, S. Arfaoui, A. Mitiche, Y. Ouakrim, A. Fuentes, G. Richardson, N. Mezghani

Medicine

Medicine

Producción científica: Capítulo en Libro/Reporte/Acta de conferencia › Contribución a la conferencia

1 Cita (Scopus)

Resumen

The purpose of this study is to investigate a method to select a set of knee kinematic data features to characterize surgical vs nonsurgical arthroplasty subjects. The kinematic features are generated from 3D knee kinematic data patterns, namely, rotations of flexion-extension, abduction-adduction, and tibial internal-external recorded during a walking task on a dedicated treadmill. The discrimination features are selected using three types of statistical complexity measures: the Fisher discriminant ratio, volume of overlap region, and feature efficiency. The interclass distance measurements which the features thus selected induce demonstrate their effectiveness to characterize surgical and nonsurgical subjects for arthroplasty.

Idioma original	English
Título de la publicación alojada	BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
Editores	Giovanni Saggio, Hugo Gamboa, Ana Fred, Sergi Bermudez i Badia
Editorial	SciTePress
Páginas	176-181
Número de páginas	6
ISBN (versión digital)	9789897582790
DOI	https://doi.org/10.5220/0006586601760181
Estado	Published - 2018
Evento	11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018 - Funchal, Madeira, Portugal Duración: ene. 19 2018 → ene. 21 2018

Serie de la publicación

Nombre	BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
Volumen	4

Conference

Conference	11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
País/Territorio	Portugal
Ciudad	Funchal, Madeira
Período	1/19/18 → 1/21/18

Nota bibliográfica

Funding Information:
This research was supported in part by the Natural Sciences and Engineering Research Council Grant (RGPIN-2015-03853) and the Canada Research Chair on Biomedical Data Mining (950-231214). The authors would like to thank Hilary Mac Donald and Tim Parlee for the kinematic data collection.

Publisher Copyright:
Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

ASJC Scopus Subject Areas

Signal Processing
Biomedical Engineering
Electrical and Electronic Engineering

Acceder al documento

10.5220/0006586601760181

Otros archivos y enlaces

Citar esto

Ben Arous, M. A., Dunbar, M., Arfaoui, S., Mitiche, A., Ouakrim, Y., Fuentes, A., Richardson, G., & Mezghani, N. (2018). Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization. En G. Saggio, H. Gamboa, A. Fred, & S. Bermudez i Badia (Eds.), BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018 (pp. 176-181). (BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018; Vol. 4). SciTePress. https://doi.org/10.5220/0006586601760181

Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization. / Ben Arous, M. A.; Dunbar, M.; Arfaoui, S. et al.
BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018. ed. / Giovanni Saggio; Hugo Gamboa; Ana Fred; Sergi Bermudez i Badia. SciTePress, 2018. p. 176-181 (BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018; Vol. 4).

Producción científica: Capítulo en Libro/Reporte/Acta de conferencia › Contribución a la conferencia

Ben Arous, MA, Dunbar, M, Arfaoui, S, Mitiche, A, Ouakrim, Y, Fuentes, A, Richardson, G & Mezghani, N 2018, Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization. En G Saggio, H Gamboa, A Fred & S Bermudez i Badia (eds.), BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018. BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018, vol. 4, SciTePress, pp. 176-181, 11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018, Funchal, Madeira, Portugal, 1/19/18. https://doi.org/10.5220/0006586601760181

Ben Arous MA, Dunbar M, Arfaoui S, Mitiche A, Ouakrim Y, Fuentes A et al. Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization. En Saggio G, Gamboa H, Fred A, Bermudez i Badia S, editores, BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018. SciTePress. 2018. p. 176-181. (BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018). doi: 10.5220/0006586601760181

Ben Arous, M. A. ; Dunbar, M. ; Arfaoui, S. et al. / Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization. BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018. editor / Giovanni Saggio ; Hugo Gamboa ; Ana Fred ; Sergi Bermudez i Badia. SciTePress, 2018. pp. 176-181 (BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018).

@inproceedings{351fb86c96624d2f86100310ecede5ba,

title = "Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization",

abstract = "The purpose of this study is to investigate a method to select a set of knee kinematic data features to characterize surgical vs nonsurgical arthroplasty subjects. The kinematic features are generated from 3D knee kinematic data patterns, namely, rotations of flexion-extension, abduction-adduction, and tibial internal-external recorded during a walking task on a dedicated treadmill. The discrimination features are selected using three types of statistical complexity measures: the Fisher discriminant ratio, volume of overlap region, and feature efficiency. The interclass distance measurements which the features thus selected induce demonstrate their effectiveness to characterize surgical and nonsurgical subjects for arthroplasty.",

author = "{Ben Arous}, {M. A.} and M. Dunbar and S. Arfaoui and A. Mitiche and Y. Ouakrim and A. Fuentes and G. Richardson and N. Mezghani",

note = "Funding Information: This research was supported in part by the Natural Sciences and Engineering Research Council Grant (RGPIN-2015-03853) and the Canada Research Chair on Biomedical Data Mining (950-231214). The authors would like to thank Hilary Mac Donald and Tim Parlee for the kinematic data collection. Publisher Copyright: Copyright {\textcopyright} 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved; 11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018 ; Conference date: 19-01-2018 Through 21-01-2018",

year = "2018",

doi = "10.5220/0006586601760181",

language = "English",

series = "BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018",

publisher = "SciTePress",

pages = "176--181",

editor = "Giovanni Saggio and Hugo Gamboa and Ana Fred and {Bermudez i Badia}, Sergi",

booktitle = "BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018",

}

TY - GEN

T1 - Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization

AU - Ben Arous, M. A.

AU - Dunbar, M.

AU - Arfaoui, S.

AU - Mitiche, A.

AU - Ouakrim, Y.

AU - Fuentes, A.

AU - Richardson, G.

AU - Mezghani, N.

N1 - Funding Information: This research was supported in part by the Natural Sciences and Engineering Research Council Grant (RGPIN-2015-03853) and the Canada Research Chair on Biomedical Data Mining (950-231214). The authors would like to thank Hilary Mac Donald and Tim Parlee for the kinematic data collection. Publisher Copyright: Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

PY - 2018

Y1 - 2018

N2 - The purpose of this study is to investigate a method to select a set of knee kinematic data features to characterize surgical vs nonsurgical arthroplasty subjects. The kinematic features are generated from 3D knee kinematic data patterns, namely, rotations of flexion-extension, abduction-adduction, and tibial internal-external recorded during a walking task on a dedicated treadmill. The discrimination features are selected using three types of statistical complexity measures: the Fisher discriminant ratio, volume of overlap region, and feature efficiency. The interclass distance measurements which the features thus selected induce demonstrate their effectiveness to characterize surgical and nonsurgical subjects for arthroplasty.

AB - The purpose of this study is to investigate a method to select a set of knee kinematic data features to characterize surgical vs nonsurgical arthroplasty subjects. The kinematic features are generated from 3D knee kinematic data patterns, namely, rotations of flexion-extension, abduction-adduction, and tibial internal-external recorded during a walking task on a dedicated treadmill. The discrimination features are selected using three types of statistical complexity measures: the Fisher discriminant ratio, volume of overlap region, and feature efficiency. The interclass distance measurements which the features thus selected induce demonstrate their effectiveness to characterize surgical and nonsurgical subjects for arthroplasty.

UR - http://www.scopus.com/inward/record.url?scp=85051745416&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85051745416&partnerID=8YFLogxK

U2 - 10.5220/0006586601760181

DO - 10.5220/0006586601760181

M3 - Conference contribution

AN - SCOPUS:85051745416

T3 - BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018

SP - 176

EP - 181

BT - BIOSIGNALS 2018 - 11th International Conference on Bio-Inspired Systems and Signal Processing, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018

A2 - Saggio, Giovanni

A2 - Gamboa, Hugo

A2 - Fred, Ana

A2 - Bermudez i Badia, Sergi

PB - SciTePress

T2 - 11th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2018 - Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018

Y2 - 19 January 2018 through 21 January 2018

ER -

Knee kinematics feature selection for surgical and nonsurgical arthroplasty candidate characterization

Resumen

Serie de la publicación

Conference

Nota bibliográfica

ASJC Scopus Subject Areas

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto