Gait analysis platform for measuring surgery recovery

Marc Codina; Manuel Navarrete; Ashkan Rezaee; David Castells-Rufas; Maria Jesús Torrelles; Stefan Burkard; Holger Arndt; Sabine Drevet; Medhi Boudissa; Jerome Tonetti; Isabelle Marque; Alexandre Moreau-Gaudry; Armand Castillejo; Jordi Carrabina

doi:10.3233/SHTI210598

Gait analysis platform for measuring surgery recovery

Marc Codina^*, Manuel Navarrete, Ashkan Rezaee, David Castells-Rufas, Maria Jesús Torrelles, Stefan Burkard, Holger Arndt, Sabine Drevet, Medhi Boudissa, Jerome Tonetti, Isabelle Marque, Alexandre Moreau-Gaudry, Armand Castillejo, Jordi Carrabina

^*Corresponding author for this work

Research output: Chapter in Book › Chapter › Research › peer-review

4 Citations (Scopus)

Abstract

Gait analysis has evolved significantly during last years due to the great development of the Medical Internet of Things (MIoT) platforms that allow an easy integration of sensors (inertial, magnetic and pressure in our case) to the complex analytics required to compute, not only relevant parameters, but also meaningful indexes. In this paper, we extend a previous development based on a fully wireless pair of insoles by implementing an updated version with more reliable and user-friendly devices, smartphone app and web front-end and back-end. We also extend previous work focused on fall analysis (with the corresponding fall risk index or FRI) with the proposal of a new surgery recovery index (SRI) to account for the individual speed recovery speed that can be measured either at clinical facilities or at home in a telemedicine environment or while doing daily life activities. This new index can be personalized for different types of surgeries that affect gait such as hip, knee, etc. This paper presents the case of hip recovery and is built on top of the clinical standard SPPB test and allows obtaining quantitative parameters directly from the sensors.

Original language	English
Title of host publication	pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health
Editors	Bernd Blobel, Mauro Giacomini
Pages	199-204
Number of pages	6
ISBN (Electronic)	9781643682266
DOIs	https://doi.org/10.3233/SHTI210598
Publication status	Published - 27 Oct 2021

Publication series

Name	Studies in Health Technology and Informatics
Volume	285
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Keywords

Gait Analysis
Hip surgery recovery
Insoles
Medical Internet-of-Things
Recovery Index

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10.3233/SHTI210598

Cite this

Codina, M., Navarrete, M., Rezaee, A., Castells-Rufas, D., Torrelles, M. J., Burkard, S., Arndt, H., Drevet, S., Boudissa, M., Tonetti, J., Marque, I., Moreau-Gaudry, A., Castillejo, A., & Carrabina, J. (2021). Gait analysis platform for measuring surgery recovery. In B. Blobel, & M. Giacomini (Eds.), pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health (pp. 199-204). (Studies in Health Technology and Informatics; Vol. 285). https://doi.org/10.3233/SHTI210598

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title = "Gait analysis platform for measuring surgery recovery",

abstract = "Gait analysis has evolved significantly during last years due to the great development of the Medical Internet of Things (MIoT) platforms that allow an easy integration of sensors (inertial, magnetic and pressure in our case) to the complex analytics required to compute, not only relevant parameters, but also meaningful indexes. In this paper, we extend a previous development based on a fully wireless pair of insoles by implementing an updated version with more reliable and user-friendly devices, smartphone app and web front-end and back-end. We also extend previous work focused on fall analysis (with the corresponding fall risk index or FRI) with the proposal of a new surgery recovery index (SRI) to account for the individual speed recovery speed that can be measured either at clinical facilities or at home in a telemedicine environment or while doing daily life activities. This new index can be personalized for different types of surgeries that affect gait such as hip, knee, etc. This paper presents the case of hip recovery and is built on top of the clinical standard SPPB test and allows obtaining quantitative parameters directly from the sensors.",

keywords = "Gait Analysis, Hip surgery recovery, Insoles, Medical Internet-of-Things, Recovery Index",

author = "Marc Codina and Manuel Navarrete and Ashkan Rezaee and David Castells-Rufas and Torrelles, {Maria Jes{\'u}s} and Stefan Burkard and Holger Arndt and Sabine Drevet and Medhi Boudissa and Jerome Tonetti and Isabelle Marque and Alexandre Moreau-Gaudry and Armand Castillejo and Jordi Carrabina",

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year = "2021",

month = oct,

day = "27",

doi = "10.3233/SHTI210598",

language = "English",

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Codina, M, Navarrete, M, Rezaee, A, Castells-Rufas, D, Torrelles, MJ, Burkard, S, Arndt, H, Drevet, S, Boudissa, M, Tonetti, J, Marque, I, Moreau-Gaudry, A, Castillejo, A & Carrabina, J 2021, Gait analysis platform for measuring surgery recovery. in B Blobel & M Giacomini (eds), pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health. Studies in Health Technology and Informatics, vol. 285, pp. 199-204. https://doi.org/10.3233/SHTI210598

Gait analysis platform for measuring surgery recovery. / Codina, Marc; Navarrete, Manuel; Rezaee, Ashkan et al.
pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health. ed. / Bernd Blobel; Mauro Giacomini. 2021. p. 199-204 (Studies in Health Technology and Informatics; Vol. 285).

Research output: Chapter in Book › Chapter › Research › peer-review

TY - CHAP

T1 - Gait analysis platform for measuring surgery recovery

AU - Codina, Marc

AU - Navarrete, Manuel

AU - Rezaee, Ashkan

AU - Castells-Rufas, David

AU - Torrelles, Maria Jesús

AU - Burkard, Stefan

AU - Arndt, Holger

AU - Drevet, Sabine

AU - Boudissa, Medhi

AU - Tonetti, Jerome

AU - Marque, Isabelle

AU - Moreau-Gaudry, Alexandre

AU - Castillejo, Armand

AU - Carrabina, Jordi

PY - 2021/10/27

Y1 - 2021/10/27

N2 - Gait analysis has evolved significantly during last years due to the great development of the Medical Internet of Things (MIoT) platforms that allow an easy integration of sensors (inertial, magnetic and pressure in our case) to the complex analytics required to compute, not only relevant parameters, but also meaningful indexes. In this paper, we extend a previous development based on a fully wireless pair of insoles by implementing an updated version with more reliable and user-friendly devices, smartphone app and web front-end and back-end. We also extend previous work focused on fall analysis (with the corresponding fall risk index or FRI) with the proposal of a new surgery recovery index (SRI) to account for the individual speed recovery speed that can be measured either at clinical facilities or at home in a telemedicine environment or while doing daily life activities. This new index can be personalized for different types of surgeries that affect gait such as hip, knee, etc. This paper presents the case of hip recovery and is built on top of the clinical standard SPPB test and allows obtaining quantitative parameters directly from the sensors.

AB - Gait analysis has evolved significantly during last years due to the great development of the Medical Internet of Things (MIoT) platforms that allow an easy integration of sensors (inertial, magnetic and pressure in our case) to the complex analytics required to compute, not only relevant parameters, but also meaningful indexes. In this paper, we extend a previous development based on a fully wireless pair of insoles by implementing an updated version with more reliable and user-friendly devices, smartphone app and web front-end and back-end. We also extend previous work focused on fall analysis (with the corresponding fall risk index or FRI) with the proposal of a new surgery recovery index (SRI) to account for the individual speed recovery speed that can be measured either at clinical facilities or at home in a telemedicine environment or while doing daily life activities. This new index can be personalized for different types of surgeries that affect gait such as hip, knee, etc. This paper presents the case of hip recovery and is built on top of the clinical standard SPPB test and allows obtaining quantitative parameters directly from the sensors.

KW - Gait Analysis

KW - Hip surgery recovery

KW - Insoles

KW - Medical Internet-of-Things

KW - Recovery Index

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U2 - 10.3233/SHTI210598

DO - 10.3233/SHTI210598

M3 - Chapter

C2 - 34734874

AN - SCOPUS:85120651698

T3 - Studies in Health Technology and Informatics

SP - 199

EP - 204

BT - pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health

A2 - Blobel, Bernd

A2 - Giacomini, Mauro

ER -

Codina M, Navarrete M, Rezaee A, Castells-Rufas D, Torrelles MJ, Burkard S et al. Gait analysis platform for measuring surgery recovery. In Blobel B, Giacomini M, editors, pHealth 2021 - Proceedings of the 18th International Conference on Wearable Micro and Nano Technologies for Personalized Health. 2021. p. 199-204. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI210598

Gait analysis platform for measuring surgery recovery

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