Search results for "Forward"

showing 10 items of 280 documents

CATCHING FALLING OBJECTS: THE ROLE OF THE CEREBELLUM IN PROCESSING SENSORY-MOTOR ERRORS THAT MAY INFLUENCE UPDATING OF FEEDFORWARD COMMANDS. AN fMRI …

2011

Import JabRef | WosArea Neurosciences and Neurology; International audience; The human motor system continuously adapts to changes in the environment by comparing differences between the brain's predicted outcome of a certain behavior and the observed outcome. This discrepancy signal triggers a sensory-motor error and it is assumed that the cerebellum is a key structure in updating this error and associated feedforward commands. Using fMRI, the aim of the present study was to determine the main cerebellar structures that are involved in the processing of sensory-motor errors and in updating feedforward commands when simply catching a falling ball without displacement of the hand. Subjects o…

AdultMaleCORTEXREPRESENTATIONgenetic structuresTRANSFORMATIONSMovementSpeech recognitionREACHING MOVEMENTS[ SCCO.PSYC ] Cognitive science/PsychologyImage processingSensory systemBrain mappingMECHANISMS03 medical and health sciences0302 clinical medicineCerebellumMotor systemImage Processing Computer-AssistedHumansADAPTATION030304 developmental biologyARM MOVEMENTSNeuronsBrain Mapping0303 health sciencesCommunicationbusiness.industry[SCCO.NEUR]Cognitive science/NeuroscienceGeneral NeuroscienceFeed forwardGRIPCognitionHUMAN BRAINMagnetic Resonance ImagingFunctional imagingbody regionsnervous system[SCCO.PSYC]Cognitive science/Psychology[ SCCO.NEUR ] Cognitive science/NeuroscienceBall (bearing)INTERNAL-MODELSbusinessPsychologyhuman activitiesPsychomotor Performance030217 neurology & neurosurgerypsychological phenomena and processes
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Causal transfer function analysis to describe closed loop interactions between cardiovascular and cardiorespiratory variability signals

2004

Although the concept of transfer function is intrinsically related to an input-output relationship, the traditional and widely used estimation method merges both feedback and feedforward interactions between the two analyzed signals. This limitation may endanger the reliability of transfer function analysis in biological systems characterized by closed loop interactions. In this study, a method for estimating the transfer function between closed loop interacting signals was proposed and validated in the field of cardiovascular and cardiorespiratory variability. The two analyzed signals x and y were described by a bivariate autoregressive model, and the causal transfer function from x to y w…

AdultMaleGeneral Computer ScienceLinear transfer functionBlood PressureBivariate analysisTransfer functionModels BiologicalFeedbackCausality (physics)Cardiovascular Physiological PhenomenaControl theoryCoherence (signal processing)HumansComputer SimulationLungMathematicsComputer Science (all)Linear modelFeed forwardReproducibility of ResultsRegression analysisHeartAutoregressive modelCardiovascular controlLinear ModelsRespiratory Physiological PhenomenaRegression AnalysisFemaleCoherenceAlgorithmsBiotechnology
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''Modulation of Anticipatory Postural Activity For Multiple Conditions of A Whole-body Pointing Task''

2012

Tolambiya, A. | Chiovetto, E. | Pozzo, T. | Thomas, E.; International audience; ''This is a study on associated postural activities during the anticipatory segments of a multijoint movement. Several previous studies have shown that they are task dependant. The previous studies, however, have mostly been limited in demonstrating the presence of modulation for one task condition, that is, one aspect such as the distance of the target or the direction of reaching. Real-life activities like whole-body pointing, however, can vary in several ways. How specific is the adaptation of the postural activities for the diverse possibilities of a whole-body pointing task? We used a classification paradig…

AdultMalemedicine.medical_specialtyCORTEXSupport Vector MachineMovementPostureEMG ANALYSISAdaptation (eye)CLASSIFICATIONTask (project management)Physical medicine and rehabilitationModulation (music)medicineMotor activity''VOLUNTARY MOVEMENTSCommunicationCOORDINATIONbusiness.industryMovement (music)General NeuroscienceTARGET DISTANCEFeed forwardMotor controlBrainElectroencephalographyHUMANSAnticipation PsychologicalCLASSIFICATION''EQUILIBRIUMADJUSTMENTS[ SCCO.NEUR ] Cognitive science/NeurosciencePATTERNSVOLUNTARY MOVEMENTSbusinessPsychologyWhole bodyPsychomotor Performance
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Strength and Latency of the HP-SAP Closed Loop Variability Interactions in Subjects Prone to Develop Postural Syncope

2019

The coupling and latency between heart period (HP) and systolic arterial pressure (SAP) variability can be investigated along the two arms of the HP-SAP closed loop, namely along the baroreflex feedback from SAP to HP, and along the feedforward pathway from HP to SAP. This study investigates the HP-SAP closed loop variability interactions through cross-correlation function (CCF). Coupling strength and delay between HP and SAP variability series were monitored in 13 subjects prone to develop orthostatic syncope (SYNC, 28±9 yrs, 5 males) and in 13 subjects with no history of postural syncope (noSYNC, age: 27±8 yrs, 5 males). Analysis was carried out at rest in supine position (REST) and durin…

AdultMalemedicine.medical_specialtySupine positiongenetic structuresBlood Pressure030204 cardiovascular system & hematologyBaroreflexSyncope03 medical and health sciencesYoung Adult0302 clinical medicineHeart RateInternal medicineHeart ratemedicineHumansComputer SimulationLatency (engineering)business.industryFeed forwardPostural syncopeHeartBaroreflexAdult Blood Pressure Computer Simulation Heart Rate Humans Male Syncope Young Adult Baroreflex HeartBlood pressureCardiologybusinessClosed loop030217 neurology & neurosurgeryAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Exploring directionality in spontaneous heart period and systolic pressure variability interactions in humans: implications in the evaluation of baro…

2004

Although in physiological conditions RR interval and systolic arterial pressure (SAP) are likely to interact in a closed loop, the traditional cross-spectral analysis cannot distinguish feedback (FB) from feedforward (FF) influences. In this study, a causal approach was applied for calculating the coherence from SAP to RR ( Ks-r) and from RR to SAP ( Kr-s) and the gain and phase of the baroreflex transfer function. The method was applied, compared with the noncausal one, to RR and SAP series taken from 15 healthy young subjects in the supine position and after passive head-up tilt. For the low frequency (0.04–0.15 Hz) spectral component, the enhanced FF coupling ( Kr-s = 0.59 ± 0.21, signi…

AdultMalemedicine.medical_specialtySympathetic Nervous SystemPhysiologyPeriod (gene)PostureRR intervalBlood PressureBaroreflexHeart RateTilt-Table TestCoherence and transfer functionFeedback and feedforward mechanismPhysiology (medical)Internal medicineHumansMedicineDirectionalityNonbaroreflex interactionFeedback Physiologicalbusiness.industryModels CardiovascularCardiovascular regulationHeartVagus NerveBaroreflexBlood pressureCirculatory systemCardiologySystolic arterial pressureFemaleCross-spectral analysiCardiology and Cardiovascular MedicinebusinessClosed loopAmerican Journal of Physiology-Heart and Circulatory Physiology
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Balance control in aging: improvements in anticipatory postural adjustments and updating of internal models

2015

International audience; Postural stability of older subjects can be estimated during orthostatic equilibrium. However, dynamic equilibrium is also important to investigate risks of fall. It implies different interpretations of measures given by force plates. Same dependant variables (e.g. center of pressure displacement) cannot be interpreted the same ways depending of the type of equilibrium that is investigated. In particular, sways increases during dynamic equilibrium and before movement execution may reflect an improvement of feedforward control.

Agingmedicine.medical_specialty[ INFO ] Computer Science [cs]MovementPostureGeriatric rehabilitationOrthostatic intoleranceAnticipatory postural adjustments[INFO] Computer Science [cs]Orthostatic vital signsCenter of pressure (terrestrial locomotion)Control theoryCorrespondencePostural BalanceHumansMedicine[INFO]Computer Science [cs]Force platformGeriatric AssessmentPostural BalanceDynamic equilibriumAgedbusiness.industryFeed forwardmedicine.diseaseBalance functionOrthostatic IntolerancePhysical therapyAccidental FallsGeriatrics and GerontologyDependantbusinessBMC Geriatrics
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Efficient pruning of multilayer perceptrons using a fuzzy sigmoid activation function

2006

This Letter presents a simple and powerful pruning method for multilayer feed forward neural networks based on the fuzzy sigmoid activation function presented in [E. Soria, J. Martin, G. Camps, A. Serrano, J. Calpe, L. Gomez, A low-complexity fuzzy activation function for artificial neural networks, IEEE Trans. Neural Networks 14(6) (2003) 1576-1579]. Successful performance is obtained in standard function approximation and channel equalization problems. Pruning allows to reduce network complexity considerably, achieving a similar performance to that obtained by unpruned networks.

Artificial neural networkComputer sciencebusiness.industryTime delay neural networkCognitive NeuroscienceActivation functionRectifier (neural networks)PerceptronFuzzy logicComputer Science ApplicationsArtificial IntelligenceMultilayer perceptronFeedforward neural networkPruning (decision trees)Artificial intelligenceTypes of artificial neural networksbusinessNeurocomputing
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A COMPARATIVE STUDY OF PHENOMENOLOGICAL MODELS OF MR BRAKE BASED ON NEURAL NETWORKS APPROACH

2013

In this paper a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system is modeled and simulated. Two well-known phenomenological hysteresis models are explored: Bouc–Wen and Dahl ones. In particular, influence of their parameters on the response is evaluated and assessed. The next step is to introduce the artificial neural networks and discuss their application in the field of systems identification. Subsequently, two feedforward neural networks are created and trained to estimate parameters characterizing each of the MR damper models described. The semi-active suspension (SAS) system equipped with a MR brake is described and the …

Artificial neural networkMathematical modelComputer scienceControl theoryApplied MathematicsSignal ProcessingBrakeReference data (financial markets)Magnetorheological fluidExperimental dataFeedforward neural networkInformation SystemsDamperInternational Journal of Wavelets, Multiresolution and Information Processing
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Optimal Pruned K-Nearest Neighbors: OP-KNN Application to Financial Modeling

2008

The paper proposes a methodology called OP-KNN, which builds a one hidden-layer feed forward neural network, using nearest neighbors neurons with extremely small computational time. The main strategy is to select the most relevant variables beforehand, then to build the model using KNN kernels. Multi-response sparse regression (MRSR) is used as the second step in order to rank each k-th nearest neighbor and finally as a third step leave-one-out estimation is used to select the number of neighbors and to estimate the generalization performances. This new methodology is tested on a toy example and is applied to financial modeling.

Artificial neural networkRank (linear algebra)GeneralizationComputer scienceKernel (statistics)Financial modelingFeedforward neural networkRegression analysisData miningcomputer.software_genrecomputerk-nearest neighbors algorithm2008 Eighth International Conference on Hybrid Intelligent Systems
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A Multi-layer Feed Forward Neural Network Approach for Diagnosing Diabetes

2018

Diabetes is one of the worlds major health problems according to the World Health Organization. Recent surveys indicate that there is an increase in the number of diabetic patients resulting in an increase in serious complications such as heart attacks and deaths. Early diagnosis of diabetes, particularly of type 2 diabetes, is critical since it is vital for patients to get insulin treatments. However, diagnoses could be difficult especially in areas with few medical doctors. It is, therefore, a need for practical methods for the public for early detection and prevention with minimal intervention from medical professionals. A promising method for automated diagnosis is the use of artificial…

Artificial neural networkbusiness.industryComputer science02 engineering and technologyType 2 diabetes030204 cardiovascular system & hematologymedicine.diseaseMachine learningcomputer.software_genreMissing dataData set03 medical and health sciences0302 clinical medicineIntervention (counseling)Diabetes mellitus0202 electrical engineering electronic engineering information engineeringmedicineFeedforward neural network020201 artificial intelligence & image processingArtificial intelligenceMedical diagnosisbusinesscomputer2018 11th International Conference on Developments in eSystems Engineering (DeSE)
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