Mostrar el registro sencillo del ítem
dc.contributor.author | Iglesias-Martinez, Miguel E. | es_ES |
dc.contributor.author | Hernaiz-Guijarro, Moises | es_ES |
dc.contributor.author | Castro-Palacio, Juan Carlos | es_ES |
dc.contributor.author | Fernández de Córdoba, Pedro | es_ES |
dc.contributor.author | Isidro, J.M. | es_ES |
dc.contributor.author | Navarro-Pardo, Esperanza | es_ES |
dc.date.accessioned | 2021-09-11T03:31:11Z | |
dc.date.available | 2021-09-11T03:31:11Z | |
dc.date.issued | 2020-11 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/172141 | |
dc.description.abstract | [EN] The reaction times of individuals over consecutive visual stimuli have been studied using an entropy-based model and a failure machinery approach. The used tools include the fast Fourier transform and a spectral entropy analysis. The results indicate that the reaction times produced by the independently responding individuals to visual stimuli appear to be correlated. The spectral analysis and the entropy of the spectrum yield that there are features of similarity in the response times of each participant and among them. Furthermore, the analysis of the mistakes made by the participants during the reaction time experiments concluded that they follow a behavior which is consistent with the MTBF (Mean Time Between Failures) model, widely used in industry for the predictive diagnosis of electrical machines and equipment. | es_ES |
dc.description.sponsorship | This research was partially supported by grant no. RTI2018-102256-B-I00 (Spain). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Mathematics | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Reaction time | es_ES |
dc.subject | Visual stimuli | es_ES |
dc.subject | Fast Fourier transform | es_ES |
dc.subject | Spectral analysis | es_ES |
dc.subject | MTBF model | es_ES |
dc.subject.classification | FISICA APLICADA | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Machinery Failure Approach and Spectral Analysis to Study the Reaction Time Dynamics over Consecutive Visual Stimuli: An Entropy-Based Model | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/math8111979 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-102256-B-I00/ES/TRANSFERENCIA DE CALOR EN FLUJOS DE PARED: CANALES Y CAPAS LIMITES/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Pura y Aplicada - Institut Universitari de Matemàtica Pura i Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada | es_ES |
dc.description.bibliographicCitation | Iglesias-Martinez, ME.; Hernaiz-Guijarro, M.; Castro-Palacio, JC.; Fernández De Córdoba, P.; Isidro, J.; Navarro-Pardo, E. (2020). Machinery Failure Approach and Spectral Analysis to Study the Reaction Time Dynamics over Consecutive Visual Stimuli: An Entropy-Based Model. Mathematics. 8(11):1-11. https://doi.org/10.3390/math8111979 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/math8111979 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 11 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 8 | es_ES |
dc.description.issue | 11 | es_ES |
dc.identifier.eissn | 2227-7390 | es_ES |
dc.relation.pasarela | S\420922 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.description.references | Thorpe, S., Fize, D., & Marlot, C. (1996). Speed of processing in the human visual system. Nature, 381(6582), 520-522. doi:10.1038/381520a0 | es_ES |
dc.description.references | Krajbich, I., Bartling, B., Hare, T., & Fehr, E. (2015). Rethinking fast and slow based on a critique of reaction-time reverse inference. Nature Communications, 6(1). doi:10.1038/ncomms8455 | es_ES |
dc.description.references | Barinaga, M. (1996). Neurons Put the Uncertainty Into Reaction Times. Science, 274(5286), 344-344. doi:10.1126/science.274.5286.344 | es_ES |
dc.description.references | Tuch, D. S., Salat, D. H., Wisco, J. J., Zaleta, A. K., Hevelone, N. D., & Rosas, H. D. (2005). Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention. Proceedings of the National Academy of Sciences, 102(34), 12212-12217. doi:10.1073/pnas.0407259102 | es_ES |
dc.description.references | Colonius, H., & Diederich, A. (2017). Measuring multisensory integration: from reaction times to spike counts. Scientific Reports, 7(1). doi:10.1038/s41598-017-03219-5 | es_ES |
dc.description.references | Ritchie, J. B., & de Beeck, H. O. (2019). Using neural distance to predict reaction time for categorizing the animacy, shape, and abstract properties of objects. Scientific Reports, 9(1). doi:10.1038/s41598-019-49732-7 | es_ES |
dc.description.references | Castro-Palacio, J. C., Fernández-de-Córdoba, P., Isidro, J. M., Navarro-Pardo, E., & Selvas Aguilar, R. (2020). Percentile Study of χ Distribution. Application to Response Time Data. Mathematics, 8(4), 514. doi:10.3390/math8040514 | es_ES |
dc.description.references | Hernaiz-Guijarro, M., Castro-Palacio, J. C., Navarro-Pardo, E., Isidro, J. M., & Fernández-de-Córdoba, P. (2019). A Probabilistic Classification Procedure Based on Response Time Analysis Towards a Quick Pre-Diagnosis of Student’s Attention Deficit. Mathematics, 7(5), 473. doi:10.3390/math7050473 | es_ES |
dc.description.references | Yamagishi, T., Matsumoto, Y., Kiyonari, T., Takagishi, H., Li, Y., Kanai, R., & Sakagami, M. (2017). Response time in economic games reflects different types of decision conflict for prosocial and proself individuals. Proceedings of the National Academy of Sciences, 114(24), 6394-6399. doi:10.1073/pnas.1608877114 | es_ES |
dc.description.references | Badau, D., Baydil, B., & Badau, A. (2018). Differences among Three Measures of Reaction Time Based on Hand Laterality in Individual Sports. Sports, 6(2), 45. doi:10.3390/sports6020045 | es_ES |
dc.description.references | Abbasi‐Kesbi, R., Memarzadeh‐Tehran, H., & Deen, M. J. (2017). Technique to estimate human reaction time based on visual perception. Healthcare Technology Letters, 4(2), 73-77. doi:10.1049/htl.2016.0106 | es_ES |
dc.description.references | Gmehlin, D., Fuermaier, A. B. M., Walther, S., Debelak, R., Rentrop, M., Westermann, C., … Aschenbrenner, S. (2014). Intraindividual Variability in Inhibitory Function in Adults with ADHD – An Ex-Gaussian Approach. PLoS ONE, 9(12), e112298. doi:10.1371/journal.pone.0112298 | es_ES |
dc.description.references | Adamo, N., Hodsoll, J., Asherson, P., Buitelaar, J. K., & Kuntsi, J. (2018). Ex-Gaussian, Frequency and Reward Analyses Reveal Specificity of Reaction Time Fluctuations to ADHD and Not Autism Traits. Journal of Abnormal Child Psychology, 47(3), 557-567. doi:10.1007/s10802-018-0457-z | es_ES |
dc.description.references | Shahar, N., Teodorescu, A. R., Karmon-Presser, A., Anholt, G. E., & Meiran, N. (2016). Memory for Action Rules and Reaction Time Variability in Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1(2), 132-140. doi:10.1016/j.bpsc.2016.01.003 | es_ES |
dc.description.references | Castellanos, F. X., Sonuga-Barke, E. J. S., Scheres, A., Di Martino, A., Hyde, C., & Walters, J. R. (2005). Varieties of Attention-Deficit/Hyperactivity Disorder-Related Intra-Individual Variability. Biological Psychiatry, 57(11), 1416-1423. doi:10.1016/j.biopsych.2004.12.005 | es_ES |
dc.description.references | Johnson, K. A., Kelly, S. P., Bellgrove, M. A., Barry, E., Cox, M., Gill, M., & Robertson, I. H. (2007). Response variability in Attention Deficit Hyperactivity Disorder: Evidence for neuropsychological heterogeneity. Neuropsychologia, 45(4), 630-638. doi:10.1016/j.neuropsychologia.2006.03.034 | es_ES |
dc.description.references | Di Martino, A., Ghaffari, M., Curchack, J., Reiss, P., Hyde, C., Vannucci, M., … Castellanos, F. X. (2008). Decomposing Intra-Subject Variability in Children with Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry, 64(7), 607-614. doi:10.1016/j.biopsych.2008.03.008 | es_ES |
dc.description.references | Vaurio, R. G., Simmonds, D. J., & Mostofsky, S. H. (2009). Increased intra-individual reaction time variability in attention-deficit/hyperactivity disorder across response inhibition tasks with different cognitive demands. Neuropsychologia, 47(12), 2389-2396. doi:10.1016/j.neuropsychologia.2009.01.022 | es_ES |
dc.description.references | Tarantino, V., Cutini, S., Mogentale, C., & Bisiacchi, P. S. (2013). Time-on-Task in Children with ADHD: An ex-Gaussian Analysis. Journal of the International Neuropsychological Society, 19(7), 820-828. doi:10.1017/s1355617713000623 | es_ES |
dc.description.references | Moret-Tatay, C., & Perea, M. (2011). Is the go/no-go lexical decision task preferable to the yes/no task with developing readers? Journal of Experimental Child Psychology, 110(1), 125-132. doi:10.1016/j.jecp.2011.04.005 | es_ES |
dc.description.references | World Medical Association Declaration of Helsinki. (2013). JAMA, 310(20), 2191. doi:10.1001/jama.2013.281053 | es_ES |
dc.description.references | Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., & Posner, M. I. (2004). Development of attentional networks in childhood. Neuropsychologia, 42(8), 1029-1040. doi:10.1016/j.neuropsychologia.2003.12.012 | es_ES |
dc.description.references | Forster, K. I., & Forster, J. C. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35(1), 116-124. doi:10.3758/bf03195503 | es_ES |
dc.description.references | Moret-Tatay, C., Leth-Steensen, C., Irigaray, T. Q., Argimon, I. I. L., Gamermann, D., Abad-Tortosa, D., … Fernández de Córdoba Castellá, P. (2016). The Effect of Corrective Feedback on Performance in Basic Cognitive Tasks: An Analysis of RT Components. Psychologica Belgica, 56(4), 370-381. doi:10.5334/pb.240 | es_ES |
dc.description.references | MORENO-CID, A., MORET-TATAY, C., IRIGARAY, T. Q., ARGIMON, I. I. L., … MURPHY, M. (2015). THE ROLE OF AGE AND EMOTIONAL VALENCE IN WORD RECOGNITION: AN EX-GAUSSIAN ANALYSIS. Studia Psychologica, 57(2), 83-94. doi:10.21909/sp.2015.02.685 | es_ES |
dc.description.references | Moret-Tatay, C., Moreno-Cid, A., Argimon, I. I. de L., Quarti Irigaray, T., Szczerbinski, M., Murphy, M., … Fernández de Córdoba Castellá, P. (2014). The effects of age and emotional valence on recognition memory: An ex-Gaussian components analysis. Scandinavian Journal of Psychology, 55(5), 420-426. doi:10.1111/sjop.12136 | es_ES |
dc.description.references | Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the Efficiency and Independence of Attentional Networks. Journal of Cognitive Neuroscience, 14(3), 340-347. doi:10.1162/089892902317361886 | es_ES |
dc.description.references | Posner, M. I., & Dehaene, S. (1994). Attentional networks. Trends in Neurosciences, 17(2), 75-79. doi:10.1016/0166-2236(94)90078-7 | es_ES |
dc.description.references | Iglesias Martínez, M., García-Gomez, J., Sáez, C., Fernández de Córdoba, P., & Alberto Conejero, J. (2018). Feature Extraction and Similarity of Movement Detection during Sleep, Based on Higher Order Spectra and Entropy of the Actigraphy Signal: Results of the Hispanic Community Health Study/Study of Latinos. Sensors, 18(12), 4310. doi:10.3390/s18124310 | es_ES |
dc.description.references | Ho, T., & Rabitz, H. (1996). A general method for constructing multidimensional molecular potential energy surfaces fromabinitiocalculations. The Journal of Chemical Physics, 104(7), 2584-2597. doi:10.1063/1.470984 | es_ES |
dc.description.references | Castro-Palacio, J. C., Nagy, T., Bemish, R. J., & Meuwly, M. (2014). Computational study of collisions between O(3P) and NO(2Π) at temperatures relevant to the hypersonic flight regime. The Journal of Chemical Physics, 141(16), 164319. doi:10.1063/1.4897263 | es_ES |
dc.description.references | Unke, O. T., Castro-Palacio, J. C., Bemish, R. J., & Meuwly, M. (2016). Collision-induced rotational excitation in N2+(2Σg+,v=0)–Ar: Comparison of computations and experiment. The Journal of Chemical Physics, 144(22), 224307. doi:10.1063/1.4951697 | es_ES |
dc.description.references | Denis-Alpizar, O., Inostroza, N., & Castro Palacio, J. C. (2017). Rotational relaxation of CF+(X1Σ) in collision with He(1S). Monthly Notices of the Royal Astronomical Society, 473(2), 1438-1443. doi:10.1093/mnras/stx2422 | es_ES |
dc.description.references | Castro-Palacio, J. C., Bemish, R. J., & Meuwly, M. (2015). Communication: Equilibrium rate coefficients from atomistic simulations: The O(3P) + NO(2Π) → O2(X3Σg−) + N(4S) reaction at temperatures relevant to the hypersonic flight regime. The Journal of Chemical Physics, 142(9), 091104. doi:10.1063/1.4913975 | es_ES |
dc.description.references | Unke, O. T., & Meuwly, M. (2017). Toolkit for the Construction of Reproducing Kernel-Based Representations of Data: Application to Multidimensional Potential Energy Surfaces. Journal of Chemical Information and Modeling, 57(8), 1923-1931. doi:10.1021/acs.jcim.7b00090 | es_ES |
dc.description.references | Ferreira, F. J. T. E., Baoming, G., & de Almeida, A. T. (2016). Reliability and Operation of High-Efficiency Induction Motors. IEEE Transactions on Industry Applications, 52(6), 4628-4637. doi:10.1109/tia.2016.2600677 | es_ES |
dc.description.references | Tavner, P., Ran, L., Penman, J., & Sedding, H. (2008). Condition Monitoring of Rotating Electrical Machines. doi:10.1049/pbpo056e | es_ES |