A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios

Biocooperative control uses both biomechanical and physiological information of the user to achieve a reliable human-robot interaction. In the context of neuromotor rehabilitation, such control can enhance rehabilitation experience and outcomes. However, the high cost and large volume of the commerc...

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Detalhes bibliográficos
Autores: Cisnal De La Rica, Ana, Antolínez, Daniel, Pérez Turiel, Javier, Fraile Marinero, Juan Carlos, Fuente López, Eusebio de la
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Recursos:Universidad de Valladolid
Repositorio:UVaDOC. Repositorio Documental de la Universidad de Valladolid
OAI Identifier:oai:uvadoc.uva.es:10324/65784
Acesso em linha:https://doi.org/10.1109/ACCESS.2023.3265898
https://uvadoc.uva.es/handle/10324/65784
Access Level:acceso abierto
Palavra-chave:Sensors
Electromyography
Electrocardiography
Sensor systems
Physiology
Biomechanics
Robots
Real-time systems
Biomedical signal processing
Wearable sensors
Biocooperative control
embedded system
neuromotor rehabilitation
real-time signal processing
wearable sensors
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spelling A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation ScenariosCisnal De La Rica, AnaAntolínez, DanielPérez Turiel, JavierFraile Marinero, Juan CarlosFuente López, Eusebio de laSensorsElectromyographyElectrocardiographySensor systemsPhysiologyBiomechanicsRobotsReal-time systemsBiomedical signal processingWearable sensorsBiocooperative controlembedded systemneuromotor rehabilitationreal-time signal processingwearable sensorsBiocooperative control uses both biomechanical and physiological information of the user to achieve a reliable human-robot interaction. In the context of neuromotor rehabilitation, such control can enhance rehabilitation experience and outcomes. However, the high cost and large volume of the commercial systems for physiological signal acquisition are major limitations for the development of such control. We present a highly versatile, low-cost and wearable embedded system that integrates the most commonly used sensors in this field: inertial measurement unit (IMU), electrocardiography (ECG), electromyography (EMG), galvanic skin response (GSR) and skin temperature (SKT) sensors. Additionally, the compact system combines wireless communication for data transmission and a high-efficiency microcontroller for real-time signal processing and control. We tested the system in two common neuromotor rehabilitation scenarios. The first is an upper-limb rehabilitation VR-based exergame, in which the patient must collect as many coins as possible. Movement recognition of the hand and arm is performed based on EMG and IMU information, respectively. The second is adaptive assistive control that adjusts the level of assistance of a wrist rehabilitation robot according to the physiological state and motor performance of the patient using GSR, ECG and SKT data. The quality of the recorded signals and the processing capacity of the system meet the needs of the two upper-limb rehabilitation applications. The wearable system is highly versatile, open, configurable and low cost, and it could promote the development of real-time biocooperative control for a wide range of neuromotor rehabilitation applications.Ministry of Science and Innovation of Spain Project IDI-20170263.IEEE Access2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1109/ACCESS.2023.3265898https://uvadoc.uva.es/handle/10324/65784reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolidinstname:Universidad de ValladolidIngléshttps://ieeexplore.ieee.org/document/10097735info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/oai:uvadoc.uva.es:10324/657842026-06-13T12:44:47Z
dc.title.none.fl_str_mv A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
title A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
spellingShingle A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
Cisnal De La Rica, Ana
Sensors
Electromyography
Electrocardiography
Sensor systems
Physiology
Biomechanics
Robots
Real-time systems
Biomedical signal processing
Wearable sensors
Biocooperative control
embedded system
neuromotor rehabilitation
real-time signal processing
wearable sensors
title_short A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
title_full A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
title_fullStr A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
title_full_unstemmed A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
title_sort A Versatile Embedded Platform for Implementation of Biocooperative Control in Upper-Limb Neuromotor Rehabilitation Scenarios
dc.creator.none.fl_str_mv Cisnal De La Rica, Ana
Antolínez, Daniel
Pérez Turiel, Javier
Fraile Marinero, Juan Carlos
Fuente López, Eusebio de la
author Cisnal De La Rica, Ana
author_facet Cisnal De La Rica, Ana
Antolínez, Daniel
Pérez Turiel, Javier
Fraile Marinero, Juan Carlos
Fuente López, Eusebio de la
author_role author
author2 Antolínez, Daniel
Pérez Turiel, Javier
Fraile Marinero, Juan Carlos
Fuente López, Eusebio de la
author2_role author
author
author
author
dc.subject.none.fl_str_mv Sensors
Electromyography
Electrocardiography
Sensor systems
Physiology
Biomechanics
Robots
Real-time systems
Biomedical signal processing
Wearable sensors
Biocooperative control
embedded system
neuromotor rehabilitation
real-time signal processing
wearable sensors
topic Sensors
Electromyography
Electrocardiography
Sensor systems
Physiology
Biomechanics
Robots
Real-time systems
Biomedical signal processing
Wearable sensors
Biocooperative control
embedded system
neuromotor rehabilitation
real-time signal processing
wearable sensors
description Biocooperative control uses both biomechanical and physiological information of the user to achieve a reliable human-robot interaction. In the context of neuromotor rehabilitation, such control can enhance rehabilitation experience and outcomes. However, the high cost and large volume of the commercial systems for physiological signal acquisition are major limitations for the development of such control. We present a highly versatile, low-cost and wearable embedded system that integrates the most commonly used sensors in this field: inertial measurement unit (IMU), electrocardiography (ECG), electromyography (EMG), galvanic skin response (GSR) and skin temperature (SKT) sensors. Additionally, the compact system combines wireless communication for data transmission and a high-efficiency microcontroller for real-time signal processing and control. We tested the system in two common neuromotor rehabilitation scenarios. The first is an upper-limb rehabilitation VR-based exergame, in which the patient must collect as many coins as possible. Movement recognition of the hand and arm is performed based on EMG and IMU information, respectively. The second is adaptive assistive control that adjusts the level of assistance of a wrist rehabilitation robot according to the physiological state and motor performance of the patient using GSR, ECG and SKT data. The quality of the recorded signals and the processing capacity of the system meet the needs of the two upper-limb rehabilitation applications. The wearable system is highly versatile, open, configurable and low cost, and it could promote the development of real-time biocooperative control for a wide range of neuromotor rehabilitation applications.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1109/ACCESS.2023.3265898
https://uvadoc.uva.es/handle/10324/65784
url https://doi.org/10.1109/ACCESS.2023.3265898
https://uvadoc.uva.es/handle/10324/65784
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://ieeexplore.ieee.org/document/10097735
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE Access
publisher.none.fl_str_mv IEEE Access
dc.source.none.fl_str_mv reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname:Universidad de Valladolid
instname_str Universidad de Valladolid
reponame_str UVaDOC. Repositorio Documental de la Universidad de Valladolid
collection UVaDOC. Repositorio Documental de la Universidad de Valladolid
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301629

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