Search results for "artificial"

showing 10 items of 7394 documents

Pointing to a target from an upright position in human: tuning of postural responses when there is target uncertainty

2000

International audience; Human subjects performed, from a standing position, rapid hand pointings to visual targets located within or beyond the prehension space. To examine the interaction between posture and the goal-directed movement we introduced a visual double-step perturbation requiring a reprogramming of the hand movement. Trials directed towards the same spatial goal but differentiated only by the likeliness of a visual double-step were compared. The hand kinematics was not affected by the uncertainty of the visual perturbation; an increased trunk bending, however, was observed. This suggests that uncertainty constraints are integrated in a predictive manner for the optimal coordina…

AdultMaleComputer scienceKinematics050105 experimental psychologyPostural controlFingers03 medical and health sciences0302 clinical medicineHumans0501 psychology and cognitive sciencesComputer visionuncertaintypostureCommunication[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behaviorElectromyographybusiness.industry[SCCO.NEUR]Cognitive science/NeuroscienceGeneral Neuroscience05 social sciences[SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive SciencesBody movementHandProprioceptionTrunkVisual Perception[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Artificial intelligencevisual double-stepbusinessPhotic StimulationPsychomotor Performancegoal-directed movement030217 neurology & neurosurgeryNeuroscience Letters
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k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation

2011

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15. Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or …

AdultMaleComputer sciencePhotic StimulationBiomedical EngineeringBiophysicsElectroencephalographyEyeMachine learningcomputer.software_genreBrain IschemiaYoung AdultIschemiamedicineHumansEEGPredictabilityIntermittent photic stimulationK nearest neighbourPredictability mapAgedScalpLocal linearmedicine.diagnostic_testbusiness.industrySpectrum AnalysisLocal linear predictionElectroencephalographySignal Processing Computer-AssistedPattern recognitionScalp eegmedicine.anatomical_structureScalpSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaCortexLinear ModelsFemaleArtificial intelligencebusinesscomputerPhotic StimulationMedical Engineering & Physics
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Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics

2019

Resting-state connectivity, for example, based on magnetoencephalography (MEG) or electroencephalography (EEG), is a widely used method for characterizing brain networks and a promising imaging biomarker. However, there is no established standard as to which method, modality, and analysis variant is preferable and there is only limited knowledge on the reproducibility, an important prerequisite for clinical application. We conducted an MEG-/ high-density (hd)-EEG-study on 22 young healthy adults, who were measured twice in a scan/rescan design after 7 – 2 days. Reliability of resting-state (15 min, eyes-closed) connectivity in source space was calculated via intraclass correlation coefficie…

AdultMaleComputer scienceRestHigh densityElectroencephalography050105 experimental psychology03 medical and health sciences0302 clinical medicineNeural PathwaysConnectomemedicineHumans0501 psychology and cognitive sciencesResting stateReliability (statistics)Brain MappingConnectivityMEGmedicine.diagnostic_testResting state fMRIbusiness.industryGeneral NeuroscienceFunctional connectivity05 social sciencesBrainMagnetoencephalographyReproducibility of ResultsElectroencephalographyPattern recognitionMagnetoencephalographyReliabilityMagnetic Resonance ImagingHealthy Volunteersddc:616.8BenchmarkingFemalehd-EEGArtificial intelligenceNerve NetbusinessAlgorithms030217 neurology & neurosurgeryBrain Connectivity
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Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures

2001

In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of …

AdultMaleCorrelation dimensionGeneral Computer ScienceEntropySleep REMLyapunov exponentElectroencephalographysymbols.namesakeStatisticsmedicineHumansEntropy (information theory)MathematicsQuantitative Biology::Neurons and Cognitionmedicine.diagnostic_testArtificial neural networkbusiness.industrySpectral entropyEye movementElectroencephalographyPattern recognitionNonlinear systemNonlinear DynamicssymbolsNeural Networks ComputerArtificial intelligencebusinessAlgorithmsBiotechnologyBiological Cybernetics
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Surrogate data analysis of sleep electroencephalograms reveals evidence for nonlinearity

1996

We tested the hypothesis of whether sleep electroencephalographic (EEG) signals of different time windows (164 s, 82 s, 41 s and 20.5 s) are in accordance with linear stochastic models. For this purpose we analyzed the all-night sleep electroencephalogram of a healthy subject and corresponding Gaussian-rescaled phase randomized surrogates with a battery of five non-linear measures. The following nonlinear measures were implemented: largest Lyapunov exponent L1, correlation dimension D2, and the Green-Savit measures delta 2, delta 4 and delta 6. The hypothesis of linear stochastic data was rejected with high statistical significance. L1 and D2 yielded the most pronounced effects, while the G…

AdultMaleCorrelation dimensionGeneral Computer ScienceStochastic modellingModels NeurologicalLyapunov exponentElectroencephalographysymbols.namesakeStatisticsmedicineHumansMathematicsStochastic ProcessesQuantitative Biology::Neurons and Cognitionmedicine.diagnostic_testStochastic processbusiness.industryLinear modelElectroencephalographyPattern recognitionNonlinear systemNonlinear DynamicsData Interpretation StatisticalLinear ModelssymbolsSleep (system call)Artificial intelligenceSleepbusinessCyberneticsBiotechnologyBiological Cybernetics
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The dimensionality of human's electroencephalogram during sleep.

1991

In order to perform an analysis of nonlinear EEG-dynamics we investigated the EEG of ten male probands during sleep. According to Rechtschaffen and Kales (1968) we scored the sleep-EEG and applied an algorithm, proposed by Grassberger and Proccaccia (1983) to compute the correlation dimension of different sleep stages. The correlation dimension characterizes the dynamics of the EEG signal and estimates the degrees of freedom of the signal under study. We could demonstrate, that the EEG of slow wave sleep stages depicts a dimensionality, which is two units smaller than that of light or REM sleep.

AdultMaleCorrelation dimensionGeneral Computer Sciencemedia_common.quotation_subjectModels NeurologicalSleep REMElectroencephalographymedicineHumansSlow-wave sleepmedia_commonSleep Stagesmedicine.diagnostic_testbusiness.industryPattern recognitionElectroencephalographyArtificial intelligenceSleep StagesSpectrum analysisbusinessPsychologySleepBiotechnologyCurse of dimensionalityVigilance (psychology)Biological cybernetics
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Nonlinear analysis of continuous ECG during sleep I. Reconstruction.

2000

In recent years evidence has accumulated that ECG signals are of a nonlinear nature. It has been recognized that strictly periodic cardiac rhythms are not accompanied by healthy conditions but, on the contrary, by pathological states. Therefore, the application of methods from nonlinear system theory for the analysis of ECG signals has gained increasing interest. Crucial for the application of nonlinear methods is the reconstruction (embedding) of the time series in a phase space with appropriate dimension. In this study continuous ECG signals of 12 healthy subjects recorded during different sleep stages were analysed. Proper embedding dimension was determined by application of two techniqu…

AdultMaleCorrelation dimensionGeneral Computer Sciencemedicine.diagnostic_testbusiness.industryComputer sciencePoison controlPattern recognitionElectroencephalographyWhite noiseElectroencephalographyNonlinear systemDimension (vector space)Nonlinear DynamicsReference ValuesPhase spacemedicineEmbeddingHumansArtificial intelligencebusinessSleepSimulationBiotechnologyBiological cybernetics
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A Nonlinear Approach to Brain Function: Deterministic Chaos and Sleep EEG

1992

In order to perform a nonlinear dimensional analysis of the sleep electroencephalogram (EEG), we applied an algorithm proposed by Grassberger and Procaccia to calculate the correlation dimension D2 of different sleep stages under Lorazepam medication versus placebo. This correlation dimension characterizes the dynamics of the sleep EEG and it estimates the degrees of freedom of the signal under study. We demonstrate that slow-wave sleep depicts a much smaller dimensionality than light or rapid eye movement (REM) sleep, and that Lorazepam does not alter the EEG's dimensionality except in stage II and REM.

AdultMaleCorrelation dimensionRapid eye movement sleepSleep REMElectroencephalographyLorazepamHippocampusModels BiologicalPhysiology (medical)mental disordersmedicineAnimalsHumansSlow-wave sleepAuditory CortexSleep Stagesmedicine.diagnostic_testbusiness.industryBrainEye movementElectroencephalographyPattern recognitionPlacebo EffectSleep in non-human animalsElectrodes ImplantedCatsSleep StagesNeurology (clinical)Artificial intelligenceSleepbusinessPsychologyNeuroscienceCurse of dimensionalitySleep
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Identifying associations between diabetes and acute respiratory distress syndrome in patients with acute hypoxemic respiratory failure: an analysis o…

2018

Background: Diabetes mellitus is a common co-existing disease in the critically ill. Diabetes mellitus may reduce the risk of acute respiratory distress syndrome (ARDS), but data from previous studies are conflicting. The objective of this study was to evaluate associations between pre-existing diabetes mellitus and ARDS in critically ill patients with acute hypoxemic respiratory failure (AHRF). Methods: An ancillary analysis of a global, multi-centre prospective observational study (LUNG SAFE) was undertaken. LUNG SAFE evaluated all patients admitted to an intensive care unit (ICU) over a 4-week period, that required mechanical ventilation and met AHRF criteria. Patients who had their AHRF…

AdultMaleDiabetes mellituLUNG SAFEOrgan Dysfunction Scoreshumanoslnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4]Socio-culturaleOrgan Dysfunction ScoreDiabetes ComplicationsDiabetes mellituspuntuaciones de disfunción orgánicaRisk FactorsDiabetes Complicationestudios prospectivosHumansfactores de riesgoProspective StudiesHospital MortalityHypoxiamediana edadAcute hypoxemic respiratory failureAgedRespiratory Distress SyndromeancianoAcute respiratory distress syndromeResearchRespirationrespiraciónRespiratory Distress Syndrome Adultlcsh:Medical emergencies. Critical care. Intensive care. First aidlcsh:RC86-88.9Middle AgedRespiration Artificialinsuficiencia respiratoriaAcute hypoxemic respiratory failure; Acute respiratory distress syndrome; Diabetes mellitus; LUNG SAFEProspective StudieArtificialAcute hypoxemic respiratory failure; Acute respiratory distress syndrome; Diabetes mellitus; LUNG SAFE; Aged; Diabetes Complications; Diabetes Mellitus; Female; Hospital Mortality; Humans; Hypoxia; Male; Middle Aged; Organ Dysfunction Scores; Prospective Studies; Respiration Artificial; Respiratory Distress Syndrome Adult; Respiratory Insufficiency; Risk FactorsFemaleRespiratory Insufficiencymortalidad hospitalariacomplicaciones de la diabetesHuman
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The remapping of time by active tool-use

2015

Multiple, action-based space representations are each based on the extent to which action is possible toward a specific sector of space, such as near/reachable and far/unreachable. Studies on tool-use revealed how the boundaries between these representations are dynamic. Space is not only multidimensional and dynamic, but it is also known for interacting with other dimensions of magnitude, such as time. However, whether time operates on similar action-driven multiple representations and whether it can be modulated by tool-use is yet unknown. To address these issues, healthy participants performed a time bisection task in two spatial positions (near and far space) before and after an active …

AdultMaleDissociation (neuropsychology)AdolescentBisectionlcsh:MedicineTask Performance and AnalysiSpace (commercial competition)Functional LateralityTask (project management)Young AdultPosition (vector)Task Performance and AnalysisHumansComputer visionlcsh:SciencePhysicsBiochemistry Genetics and Molecular Biology (all)Multidisciplinarybusiness.industryDistance PerceptionMedicine (all)lcsh:RTime perceptionAgricultural and Biological Sciences (all)Action (philosophy)Body schemaAdolescent; Adult; Distance Perception; Female; Functional Laterality; Humans; Male; Young Adult; Task Performance and Analysis; Time Perception; Agricultural and Biological Sciences (all); Biochemistry Genetics and Molecular Biology (all); Medicine (all)Time PerceptionFemalelcsh:QArtificial intelligencebusinessResearch ArticleHuman
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