0000000000199040

AUTHOR

Juan-manuel Belda-lois

0000-0002-7648-799x

showing 5 related works from this author

Classification of healthy, Alzheimer and Parkinson populations with a multi-branch neural network

2022

Signal processing, for delimitation of the target events and parametrization, is usually required when instrumented assessment is conducted to determine an individual’s functional status. However, these procedures may rule out relevant information obtained by sensors. To prevent this, the use of models based on neural networks that automatically extract relevant features from the raw signal may improve the characterization of the functional status. Thus, the aim of the study was to determine the classification accuracy of a multi-head convolutional layered neural network (CNN) using a simple functional mobility test in people with different conditions. The raw data from an inertial sensor e…

inertial sensorparkinson’s diseaseSignal Processingalzheimer diseaseBiomedical EngineeringHealth Informaticsfunctional assessmentmulti-branch convolutional classifierUNESCO::CIENCIAS TECNOLÓGICASBiomedical Signal Processing and Control
researchProduct

A new methodology based on functional principal component analysis tostudy postural stability post-stroke

2018

[EN] Background. A major goal in stroke rehabilitation is the establishment of more effective physical therapy techniques to recover postural stability. Functional Principal Component Analysis provides greater insight into recovery trends. However, when missing values exist, obtaining functional data presents some difficulties. The purpose of this study was to reveal an alternative technique for obtaining the Functional Principal Components without requiring the conversion to functional data beforehand and to investigate this methodology to determine the effect of specific physical therapy techniques in balance recovery trends in elderly subjects with hemiplegia post-stroke. Methods: A rand…

Male030506 rehabilitationmedicine.medical_specialtymedicine.medical_treatmentINGENIERIA MECANICAFunctional Principal Component AnalysisBiophysicsPostural stabilityHemiplegiaTreatment and control groups03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationDouble-Blind MethodRombergmedicineHumansOrthopedics and Sports MedicineLeast-Squares AnalysisPostural BalanceStrokePhysical Therapy ModalitiesAgedBalance (ability)Observer VariationFunctional principal component analysisPrincipal Component AnalysisRehabilitationbusiness.industryPosturographyPosturographyHemodynamicsStroke RehabilitationReproducibility of ResultsMiddle AgedMissing datamedicine.diseaseStrokeTreatment OutcomePrincipal component analysisFemale0305 other medical sciencebusiness030217 neurology & neurosurgery
researchProduct

Functional principal component analysis as a new methodology for the analysis of the impact of two rehabilitation protocols in functional recovery af…

2014

[EN] Background: This study addressed the problem of evaluating the effectiveness of two protocols of physiotherapy for functional recovery after stroke. In particular, the study explored the use of Functional Principal Component Analysis (FPCA), a multivariate data analysis in order to assess and clarify the process of regaining independence after stroke. Methods: A randomized double-blind controlled trial was performed. Thirteen subjects with residual hemiparesis after a single stroke episode were measured in both in- and outpatient settings at a district hospital. All subjects were able to walk before suffering the stroke and were hemodynamically stable within the first week after stroke…

Malemedicine.medical_specialtyMultivariate analysismedicine.medical_treatmentINGENIERIA MECANICAHealth InformaticsPhysical medicine and rehabilitationDouble-Blind MethodFunctional principal components analysismedicineHumansStrokePhysiotherapyPhysical Therapy ModalitiesAgedFunctional principal component analysisPrincipal Component AnalysisRehabilitationbusiness.industryRehabilitationStroke RehabilitationMethodologyFunctional recoveryRecovery of Functionmedicine.diseaseFunctional recovery3. Good healthStrokePrincipal component analysisPhysical therapyFemalebusiness
researchProduct

A new methodology for Functional Principal Component Analysis from scarce data. Application to stroke rehabilitation.

2015

Functional Principal Component Analysis (FPCA) is an increasingly used methodology for analysis of biomedical data. This methodology aims to obtain Functional Principal Components (FPCs) from Functional Data (time dependent functions). However, in biomedical data, the most common scenario of this analysis is from discrete time values. Standard procedures for FPCA require obtaining the functional data from these discrete values before extracting the FPCs. The problem appears when there are missing values in a non-negligible sample of subjects, especially at the beginning or the end of the study, because this approach can compromise the analysis due to the need to extrapolate or dismiss subje…

Scarce dataFunctional principal component analysisPrincipal Component AnalysisComputer scienceProcess (engineering)Stroke RehabilitationSample (statistics)Missing datacomputer.software_genreStrokePrincipal component analysisHumansData miningcomputerAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
researchProduct

Adaptive inputs in an interface for people with Dyskinetic Cerebral Palsy: Learning and usability

2016

This study concerns the difficulty in accessing computers faced by people with Dyskinetic Cerebral Palsy (DCP). Thus diminishing their opportunities to communicate or learn. This population usually needs an alternative input human-computer interface (HCI). The paper presents an alternative multimodal HCI that incorporates a head-mounted interface and superficial electromyography sensors (sEMG). The aim of the study is to assess the usability and the suitability of these two HCI devices. Six non-disabled subjects and ten subjects with DCP participated in the iterative process in which each test follows an improvement of an input. The results indicated that for both systems, the improvements …

030506 rehabilitationEngineeringInterface (computing)INGENIERIA MECANICAHealth Informaticsdyskinesia usabilitymotor disordersCerebral palsy03 medical and health sciences0302 clinical medicinesEMGHuman–computer interactionAssistive technologyassistive technologymedicineuser-adaptationSimulationhuman-machine interactionbusiness.industryRehabilitationUsabilitymedicine.diseaseinertial sensorsAugmentative and alternative communicationHuman machine interactionaugmentative and alternative communicationCerebral palsy0305 other medical sciencebusiness030217 neurology & neurosurgeryDyskinetic cerebral palsy
researchProduct