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Biofeedback-based method for real-time fatigue monitoring of knee

2024Journal article Open access
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dc.contributor.authorFranco, Tiago
dc.contributor.authorHenriques, Pedro
dc.contributor.authorAlves, Paulo
dc.contributor.authorPereira, Maria João
dc.contributor.authorLeitão, Paulo
dc.contributor.authorAzevedo, Nelson
dc.date.accessioned2024-10-28T15:54:37Z
dc.date.available2024-10-28T15:54:37Z
dc.date.issued2024
dc.description.abstractThis paper introduces and implements a method to monitor muscle fatigue in real-time using a wearable biofeedback system to improve muscle rehabilitation treatments. The biofeedback system consists of an electromyography (EMG) sensor to capture muscle activity and two motion sensors to track knee angles. The proposed method for monitoring muscle fatigue involves three steps: (1) recognition of the movement phases during the knee extension exercise; (2) clipping of the EMG signal and calculation of fatigue-related metrics; and (3) normalization of metrics through a calibration process. An experimental session was performed with 10 healthy subjects performing 50 repetitions of the knee extension exercise. Processed data revealed changes in fatigue-related metrics, which align with existing literature. A comparison was also made between real-time and computer processing using raw data. While minor differences were noted between the two processing methods, the mobile app closely mirrored the trajectory of processed data in the cloud, ensuring reliability and consistency. This study advances remote muscle rehabilitation by quantifying muscle fatigue during treatment sessions. Thus, health professionals can tailor treatment plans based on individual patient characteristics, optimizing treatment duration, and reducing injury risk.pt_PT
dc.description.sponsorshipThis work was supported European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Portugal 2020, in the framework of the NanoStim (POCI-01-0247-FEDER-045908) project, Fundação para a Ciência e a Tecnologia under Projects UIDB/05757/2020, UIDB/00319/2020, and PhD grant 2020.05704.BD.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFranco, Tiago; Henriques, Pedro Rangel; Alves, Paulo; Pereira, Maria João; Leitão, Paulo; Azevedo, Nelson (2024). Biofeedback-based method for real-time fatigue monitoring of knee. International Journal of Online and Biomedical Engineering (iJOE). ISSN 2626-8493. 20:13, p. 60-83pt_PT
dc.identifier.doi10.3991/ijoe.v20i13.50101pt_PT
dc.identifier.eissn2626-8493
dc.identifier.urihttp://hdl.handle.net/10198/30490
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInternational Federation of Engineering Education Societies (IFEES)pt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationALGORITMI Research Center
dc.relationalterado para: Clinical Decision Support System to Electrostimulation Treatments for Muscle Rehabilitation in the Elderly Data-Driven Decision Support System for Higher Education Institutions
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectMuscle fatiguept_PT
dc.subjectBiofeedbackpt_PT
dc.subjectRemote rehabilitationpt_PT
dc.subjectReal-time monitoringpt_PT
dc.titleBiofeedback-based method for real-time fatigue monitoring of kneept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleALGORITMI Research Center
oaire.awardTitlealterado para: Clinical Decision Support System to Electrostimulation Treatments for Muscle Rehabilitation in the Elderly Data-Driven Decision Support System for Higher Education Institutions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//2020.05704.BD/PT
oaire.citation.endPage83pt_PT
oaire.citation.issue13pt_PT
oaire.citation.startPage60pt_PT
oaire.citation.titleInternational Journal of Online and Biomedical Engineering (iJOE)pt_PT
oaire.citation.volume20pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFranco
person.familyNameAlves
person.familyNamePereira
person.familyNameLeitão
person.givenNameTiago
person.givenNamePaulo
person.givenNameMaria João
person.givenNamePaulo
person.identifierUAMm8moAAAAJ&hl
person.identifierA-8390-2011
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person.identifier.ciencia-idC319-FC42-5B6B
person.identifier.ciencia-idC912-4A49-A3B3
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.orcid0000-0001-8574-4380
person.identifier.orcid0000-0002-0100-8691
person.identifier.orcid0000-0001-6323-0071
person.identifier.orcid0000-0002-2151-7944
person.identifier.ridG-5999-2011
person.identifier.scopus-author-id57223608236
person.identifier.scopus-author-id55834442100
person.identifier.scopus-author-id13907870300
person.identifier.scopus-author-id35584388900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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