1. A. Veloz, C. Moraga, A. Weinstein, L. Hernández-García, S. Chabert, R. Salas, R. Riveros, C. Bennett, H. Allende (2020). Fuzzy General Linear Modeling for Functional Magnetic Resonance Imaging Analysis (2020). IEEE Trans. Fuzzy Systems. vol 28, issue 1, pp.100-111. doi: 10.1109/TFUZZ.2019.2936807 (WOS)
  2. Oscar Valencia, Iver Cristi, Darío Ahumada, Keiny Meza, Rodrigo SalasAlejandro Weinstein, Rodrigo Guzmán-Venegas (2020) El impacto inicial con antepié incrementa la actividad muscular del gastrocnemios durante la carrera. Un estudio cuantitativo de actividad electromiográfica. The initial impact with forefoot increases the muscular activity of gastrocnemius during running. A quantitative study of electromyographic activity. Retos, vol 38, pp. 271-275. WoS


  1. D. Mellado, R. Salas, C. Saavedra, R. Torres, S. Chabert (2019). Self-Improving Generative Artificial Neural Network with novelty detection for Incremental Class Learning. Algorithms 2019, 12(10), 206. DOI: 10.3390/a12100206 (WOS)
  2. S. Chabert, J. Verdu, G. Huerta, C. Montalba, P. Cox, R. Riveros, S. Uribe, R. Salas, A. Veloz. Impact of b-value sampling scheme on Brain IVIM estimation in Healthy subjects. Journal Magnetic Resonance in Medical Sciences. Article ID mp.2019-0061, ISSN 1880-2206, doi: 10.2463/ (WOS)
  3. C. Saavedra, R. Salas, L. Bougrain. Wavelet-based semblance methods to enhance single-trial ERP detection. Computational Intelligence and Neuroscience. Article ID 8432953, 10 pages (WOS)
  4. E. Vivas, H. Allende-Cid, R. Salas and L. Bravo (2019). Polynomial and wavelet-type transfer function models to improve the  fisheries landing forecasting with exogenous variable. Entropy 2019, 21(11), 1-17 MDPI. DOI:10.3390/e21111082 WoS
  5. M. Salinas, R. Salas, D. Mellado, A. Glaría, C. Saavedra. A Computational Fractional Signal Derivative Method. Modelling and Simulation in Engineering. Research Article (10 pages), Article ID 7280306, Volume 2018. ISSN: 1687-5591 (WOS)
  6. Pavel Prado-Gutierrez, Eduardo Martínez-Montes, Alejandro Weinstein, Matías Zañartu (2019) Estimation of auditory steady-state responses based on the averaging of independent EEG epochs. Plos One 14 (1) e0206018 (ISI)
  7. Solis-Urra, Olivares-Arancibia, Suarez-Cadenas, Sanchez-Martinez, Rodriguez-Rodriguez, Ortega, Esteban-Cornejo, Sanchez-Cadenas, Castro-Piñero, VelozChabert, Saradangani, Zavala, Migueles, Quiroz, Martinez, Urzua, Cristi-Montero. Rationale, design and methods of a cross-sectional study on brain, cognition, physical activity, and fitness in schoolchildren. The Cogni-Action project: part I. BMC Pediatrics,19:260 (2019). WoS
  8. Varela-Mattatall, Tobisch, Stirnberg, Chabert, Uribe, Tejos, Stöcker, Irarrázaval, Comparison of Q-Space Reconstruction Methods for Undersampled Diffusion Spectrum Imaging Data. Magnetic Resonance in Medical Sciences. (2019) In Press. doi:10.2463/ WoS
  9. Ulloa G, Naranjo R, Allende-Cid H, Chabert S, Allende H, Circular Non-uniform Sampling Patch Inputs for CNN Applied to Multiple Sclerosis Lesion Segmentation. CIARP 2018, LNCS 11401 proceedings, pp 1—8, 2019. Springer


  1. P. Reyes-Cabrera, D. Larée, A. Weinstein and A. Jara (2018) Towards a conceptual model for the use of home healthcare medical devices: The multi-parameter monitor case. Plos One 13 (12) e0208723 (ISI)
  2. PA Warren, U Gostoli, GD Farmer, W El-Deredy, U Hahn. A re-examination of “bias” in human randomness perception. Journal of Experimental Psychology: Human Perception and Performance 44 (5), 663 (2018)
  3. EJ Hird, W El‐Deredy, A Jones, D Talmi. Temporal dissociation of salience and prediction error responses to appetitive and aversive taste. Psychophysiology 55 (2), e12976 (2018)
  4. M Craddock, E Klepousniotou, W El-Deredy, E Poliakoff, DM Lloyd. Transcranial alternating current stimulation at 10 Hz modulates response bias in the Somatic Signal Detection Task. bioRxiv, 330134 (2018)
  5. EJ Hird, AKP Jones, D Talmi, W El-Deredy. A comparison between the neural correlates of laser and electric pain stimulation and their modulation by expectation Journal of neuroscience methods 293, 117-127 (2018)
  6. Suliman Belal, James Cousins, Wael El-Deredy, Laura M. Parkes, Jules Schneider, Hikaru Tsujimura, Alexia Zoumpoulaki, Marta Perapoch, Lorena Santamaría, Penelope A. Lewis: Identification of memory reactivation during sleep by EEG classification. NeuroImage 176: 203-214 (2018)
  7. M. Salinas, R. Salas, D. Mellado, A. Glaría y C. Saavedra (2018) A Computational Fractional Signal Derivative Method. Journal of  Modelling and Simulation in Engineering. Volume 2018, Article ID 7280306, 10 pages. DOI: 10.1155/2018/7280306 (ISI)
  8. F. Plaza, R. Salas, E. Yáñez (2018). Identifying ecosystem patterns from time series of anchovy (Engraulis ringens) and sardine (Sardinops Sagax) landings in northern Chile. Published in the Journal of Statistical Computation and Simulation. doi: 0.1080/00949655.2017.1410150 (ISI)
  9. R. Torres, R.Salas, N. Bencomo, H. Astudillo (2018). An architecture based on computing with words to support runtime reconfiguration decisions of service-based systems. Published in the International Journal of Computational Intelligence Systems. Vol 11, issue 1, pp. 272-281.  doi:10.2991/ijcis.11.1.21 (IJCIS) (ISI)
  10. Richard A, Orio P, Tanré E (2018) An Integrate-and-fire Model To Generate Spike Trains With Long-range Dependence. Journal Of Computational Neuroscience 44(3):297-312. Doi: 10.1007/s10827-018-0680-1
  11. Xu K, Maidana JP, Castro S and Orio P (2018) Synchronization transition in neuronal networks composed of chaotic or non-chaotic oscillators. Scientific Reports. 8(1):8370. doi: 10.1038/s41598-018-26730-9
  12. Taramasco, C., Rodenas, T., Martinez, F., Fuentes, P., Muñoz, R., Olivares, R., De Albuquerque V., Demongeot, J. (2018). A Novel Monitoring System for Fall Detection in Older People. IEEE Access (ISI – Aceptado)
  13. Vieira, F., Cechinel, C. Munoz, R., Villarroel, R., Merino, E. , Lemos, R. (2018). Using Multimodal Data to Find Patterns in Student Presentations. In Learning Objects and Technology (LACLO), Latin American Conference on (Scopus – Aceptado)
  14. Quezada, A., Juárez-Ramírez, R., Jiménez, S., Ramírez-Noriega, A., Inzunza, S., Villarroel, R. & Munoz, R. (2018). Relations between Touch Target Size and Drag Distance in Mobile Applications for Users with Autism Spectrum Disorders. Journal of Medical Systems (ISI – Aceptado)
  15. Barcelos, T. S., Munoz, R., Villarroel, R., Merino, E., Silveira, I.F. (2018). Mathematics Learning through Computational Thinking Activities: A Systematic Literature Review. Journal of Universal Computer Science, 24(6) (ISI – To appear)
  16. Munoz, R., Becerra, C., Noël, R., Camblor, M., Barcelos, T. S., Kreisel, S., & Villarroel, R. (2018). Design, Implementation and Evaluation of a Learning Object that Supports the Mathematics Learning in Children with Autism Spectrum Disorders. CLEI Electronic Journal, 21(1), 8. (ScIELO)
  17. Munoz, R., Barcelos, T. S., & Villarroel, R. (2018). CT4All: Enhancing Computational Thinking Skills in Adolescents with Autism Spectrum Disorders. IEEE Latin America Transactions, 16(3), 909–917. (ISI)
  18. Munoz, R., Olivares, R., Taramasco, C., Villarroel, R., Soto, R., Barcelos, T. S., Merino, E., Alonso-Sánchez, M. F. (2018). Using Black Hole Algorithm to improve EEG-based Emotion Recognition. Computational Intelligence and Neuroscience, 2018, 21. (ISI)
  19. Munoz, R., Villarroel, R., Barcelos, T. S., Souza, A., Merino, E., Guiñez, R., & Silva, L. A. (2018). Development of a Software that Supports Multimodal Learning Analytics: A Case Study on Oral Presentations. Journal of Universal Computer Science, 24(2), 149–170. (ISI)
  20. Quezada, A., Juárez-Ramírez, R., Jiménez, S., Ramírez-Noriega, A., Inzunza, S., & Munoz, R. (2018). Assessing the Target’ Size and Drag Distance in Mobile Applications for Users with Autism. In World Conference on Information Systems and Technologies (pp. 1219–1228). Springer. (Scopus)