Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments

Bibliographic Details
Main Author: Alberto, Sara
Publication Date: 2021
Other Authors: Cabral, Sílvia, Proença, João, Pona-Ferreira, Filipa, Leitão, Mariana, Bouça-Machado, Raquel, Azevedo Kauppila, Linda, Veloso, António, Costa, Rui M., Ferreira, Joaquim J, Matias, Ricardo
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10451/49396
Summary: © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
id RCAP_16eacd60236165feab18ecec31e9c94e
oai_identifier_str oai:repositorio.ulisboa.pt:10451/49396
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environmentsParkinson’s diseaseGait analysisPathological gaitWearable devicesSmartphoneKinematics© The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.Background: Gait impairments are among the most common and impactful symptoms of Parkinson’s disease (PD). Recent technological advances aim to quantify these impairments using low-cost wearable systems for use in either supervised clinical consultations or long-term unsupervised monitoring of gait in ecological environments. However, very few of these wearable systems have been validated comparatively to a criterion of established validity. Objective: We developed two movement analysis solutions (3D full-body kinematics based on inertial sensors, and a smartphone application) in which validity was assessed versus the optoelectronic criterion in a population of PD patients. Methods: Nineteen subjects with PD (7 female) participated in the study (age: 62 ± 12.27 years; disease duration: 6.39 ± 3.70 years; HY: 2 ± 0.23). Each participant underwent a gait analysis whilst barefoot, at a self-selected speed, for a distance of 3 times 10 m in a straight line, assessed simultaneously with all three systems. Results: Our results show excellent agreement between either solution and the optoelectronic criterion. Both systems differentiate between PD patients and healthy controls, and between PD patients in ON or OFF medication states (normal difference distributions pooled from published research in PD patients in ON and OFF states that included an age-matched healthy control group). Fair to high waveform similarity and mean absolute errors below the mean relative orientation accuracy of the equipment were found when comparing the angular kinematics between the full-body inertial sensor-based system and the optoelectronic criterion. Conclusions: We conclude that the presented solutions produce accurate results and can capture clinically relevant parameters using commodity wearable sensors or a simple smartphone. This validation will hopefully enable the adoption of these systems for supervised and unsupervised gait analysis in clinical practice and clinical trials.Springer NatureRepositório da Universidade de LisboaAlberto, SaraCabral, SílviaProença, JoãoPona-Ferreira, FilipaLeitão, MarianaBouça-Machado, RaquelAzevedo Kauppila, LindaVeloso, AntónioCosta, Rui M.Ferreira, Joaquim JMatias, Ricardo2021-09-02T10:57:32Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/49396engBMC Neurol. 2021 Aug 28;21(1):33110.1186/s12883-021-02354-x1471-2377info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T14:36:48Zoai:repositorio.ulisboa.pt:10451/49396Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:17:00.622140Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
title Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
spellingShingle Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
Alberto, Sara
Parkinson’s disease
Gait analysis
Pathological gait
Wearable devices
Smartphone
Kinematics
title_short Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
title_full Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
title_fullStr Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
title_full_unstemmed Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
title_sort Validation of quantitative gait analysis systems for Parkinson’s disease for use in supervised and unsupervised environments
author Alberto, Sara
author_facet Alberto, Sara
Cabral, Sílvia
Proença, João
Pona-Ferreira, Filipa
Leitão, Mariana
Bouça-Machado, Raquel
Azevedo Kauppila, Linda
Veloso, António
Costa, Rui M.
Ferreira, Joaquim J
Matias, Ricardo
author_role author
author2 Cabral, Sílvia
Proença, João
Pona-Ferreira, Filipa
Leitão, Mariana
Bouça-Machado, Raquel
Azevedo Kauppila, Linda
Veloso, António
Costa, Rui M.
Ferreira, Joaquim J
Matias, Ricardo
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Alberto, Sara
Cabral, Sílvia
Proença, João
Pona-Ferreira, Filipa
Leitão, Mariana
Bouça-Machado, Raquel
Azevedo Kauppila, Linda
Veloso, António
Costa, Rui M.
Ferreira, Joaquim J
Matias, Ricardo
dc.subject.por.fl_str_mv Parkinson’s disease
Gait analysis
Pathological gait
Wearable devices
Smartphone
Kinematics
topic Parkinson’s disease
Gait analysis
Pathological gait
Wearable devices
Smartphone
Kinematics
description © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-02T10:57:32Z
2021
2021-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/49396
url http://hdl.handle.net/10451/49396
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv BMC Neurol. 2021 Aug 28;21(1):331
10.1186/s12883-021-02354-x
1471-2377
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833601651198394368