Motion sensors for Knee angle recognition in muscle rehabilitation solutions
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/27138 |
Resumo: | The progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient’s home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient’s movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity O(1) were tested to improve the signal’s noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor. |
id |
RCAP_c9a49b41708ea8e36dc98aabaee8de24 |
---|---|
oai_identifier_str |
oai:bibliotecadigital.ipb.pt:10198/27138 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Motion sensors for Knee angle recognition in muscle rehabilitation solutionsIMU sensorAlgorithmic complexityKnee angleMuscle rehabilitationWearable systemThe progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient’s home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient’s movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity O(1) were tested to improve the signal’s noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor.MDPIBiblioteca Digital do IPBFranco, TiagoOliveira, Leonardo Sestrem deHenriques, Pedro RangelAlves, PauloPereira, Maria JoãoBrandão, DiegoLeitão, PauloSilva, Alfredo2023-02-23T14:20:07Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/27138engFranco, Tiago; Sestrem de Oliveira, Leonardo; Henriques, Pedro Rangel; Alves, Paulo; Pereira, Maria João; Brandão, Diego; Leitão, Paulo; Silva, Alfredo (2022). Motion sensors for Knee angle recognition in muscle rehabilitation solutions. Sensors. 760510.3390/s22197605info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-21T11:00:14Zoai:bibliotecadigital.ipb.pt:10198/27138Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:17:29.091508Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
title |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
spellingShingle |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions Franco, Tiago IMU sensor Algorithmic complexity Knee angle Muscle rehabilitation Wearable system |
title_short |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
title_full |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
title_fullStr |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
title_full_unstemmed |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
title_sort |
Motion sensors for Knee angle recognition in muscle rehabilitation solutions |
author |
Franco, Tiago |
author_facet |
Franco, Tiago Oliveira, Leonardo Sestrem de Henriques, Pedro Rangel Alves, Paulo Pereira, Maria João Brandão, Diego Leitão, Paulo Silva, Alfredo |
author_role |
author |
author2 |
Oliveira, Leonardo Sestrem de Henriques, Pedro Rangel Alves, Paulo Pereira, Maria João Brandão, Diego Leitão, Paulo Silva, Alfredo |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Franco, Tiago Oliveira, Leonardo Sestrem de Henriques, Pedro Rangel Alves, Paulo Pereira, Maria João Brandão, Diego Leitão, Paulo Silva, Alfredo |
dc.subject.por.fl_str_mv |
IMU sensor Algorithmic complexity Knee angle Muscle rehabilitation Wearable system |
topic |
IMU sensor Algorithmic complexity Knee angle Muscle rehabilitation Wearable system |
description |
The progressive loss of functional capacity due to aging is a serious problem that can compromise human locomotion capacity, requiring the help of an assistant and reducing independence. The NanoStim project aims to develop a system capable of performing treatment with electrostimulation at the patient’s home, reducing the number of consultations. The knee angle is one of the essential attributes in this context, helping understand the patient’s movement during the treatment session. This article presents a wearable system that recognizes the knee angle through IMU sensors. The hardware chosen for the wearables are low cost, including an ESP32 microcontroller and an MPU-6050 sensor. However, this hardware impairs signal accuracy in the multitasking environment expected in rehabilitation treatment. Three optimization filters with algorithmic complexity O(1) were tested to improve the signal’s noise. The complementary filter obtained the best result, presenting an average error of 0.6 degrees and an improvement of 77% in MSE. Furthermore, an interface in the mobile app was developed to respond immediately to the recognized movement. The systems were tested with volunteers in a real environment and could successfully measure the movement performed. In the future, it is planned to use the recognized angle with the electromyography sensor. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z 2023-02-23T14:20:07Z |
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/10198/27138 |
url |
http://hdl.handle.net/10198/27138 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Franco, Tiago; Sestrem de Oliveira, Leonardo; Henriques, Pedro Rangel; Alves, Paulo; Pereira, Maria João; Brandão, Diego; Leitão, Paulo; Silva, Alfredo (2022). Motion sensors for Knee angle recognition in muscle rehabilitation solutions. Sensors. 7605 10.3390/s22197605 |
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 |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799135464886632448 |