| Monitoring the depth of anesthesia using entropy features and an artificial neural network R Shalbaf, H Behnam, JW Sleigh, A Steyn-Ross, LJ Voss Journal of neuroscience methods 218 (1), 17-24, 2013 | 91 | 2013 |
| Monitoring the depth of anesthesia using a new adaptive neurofuzzy system A Shalbaf, M Saffar, JW Sleigh, R Shalbaf IEEE journal of biomedical and health informatics 22 (3), 671-677, 2017 | 81 | 2017 |
| Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables R Shalbaf, H Behnam, H Jelveh Moghadam Cognitive Neurodynamics 9, 41-51, 2015 | 68 | 2015 |
| Measuring the effects of sevoflurane on electroencephalogram using sample entropy R Shalbaf, H Behnam, J Sleigh, L Voss Acta Anaesthesiologica Scandinavica 56 (7), 880-889, 2012 | 53 | 2012 |
| Characterizing awake and anesthetized states using a dimensionality reduction method M Mirsadeghi, H Behnam, R Shalbaf, H Jelveh Moghadam Journal of medical systems 40, 1-8, 2016 | 45 | 2016 |
| Frontal–temporal functional connectivity of EEG signal by standardized permutation mutual information during anesthesia F Afshani, A Shalbaf, R Shalbaf, J Sleigh Cognitive neurodynamics 13, 531-540, 2019 | 38 | 2019 |
| Frontal-temporal synchronization of EEG signals quantified by order patterns cross recurrence analysis during propofol anesthesia R Shalbaf, H Behnam, JW Sleigh, DA Steyn-Ross, ML Steyn-Ross IEEE Transactions on Neural Systems and Rehabilitation Engineering 23 (3 …, 2014 | 37 | 2014 |
| Using the Hilbert–Huang transform to measure the electroencephalographic effect of propofol R Shalbaf, H Behnam, JW Sleigh, LJ Voss Physiological measurement 33 (2), 271, 2012 | 32 | 2012 |
| Monitoring the level of hypnosis using a hierarchical SVM system A Shalbaf, R Shalbaf, M Saffar, J Sleigh Journal of Clinical Monitoring and Computing 34, 331-338, 2020 | 31 | 2020 |
| Non-linear entropy analysis in EEG to predict treatment response to repetitive transcranial magnetic stimulation in depression R Shalbaf, C Brenner, C Pang, DM Blumberger, J Downar, ZJ Daskalakis, ... Frontiers in Pharmacology 9, 1188, 2018 | 22 | 2018 |
| Extracting a seizure intensity index from one-channel EEG signal using bispectral and detrended fluctuation analysis PT Hosseini, R Shalbaf, AM Nasrabadi journal of biomedical science and engineering, 2010 | 20 | 2010 |
| Assessment of anesthesia depth using effective brain connectivity based on transfer entropy on EEG signal N Sanjari, A Shalbaf, R Shalbaf, J Sleigh Basic and clinical neuroscience 12 (2), 269, 2021 | 14 | 2021 |
| Epilepsy detection using detrended fluctuation analysis R Shalbaf, PT Hosseini, M Analoui 2009 International Conference on Wavelet Analysis and Pattern Recognition …, 2009 | 10 | 2009 |
| Automatic computation of left ventricular volume changes over a cardiac cycle from echocardiography images by nonlinear dimensionality reduction Z Alizadeh Sani, A Shalbaf, H Behnam, R Shalbaf Journal of Digital Imaging 28, 91-98, 2015 | 9 | 2015 |
| Order patterns recurrence analysis of electroencephalogram during sevoflurane anesthesia R Shalbaf, H Behnam, J Sleigh Biomedical Engineering: Applications, Basis and Communications 27 (05), 1550049, 2015 | 4 | 2015 |
| The brain function index as a depth of anesthesia indicator using complexity measures R Shalbaf, H Behnam, HJ Moghadam, A Mehrnam, M Sadaghiani 2013 IEEE Conference on Systems, Process & Control (ICSPC), 68-72, 2013 | 4 | 2013 |
| Depth of anesthesia indicator using combination of complexity and frequency measures R Shalbaf, AH Mehrnam, H Behnam 2014 21th Iranian Conference on Biomedical Engineering (ICBME), 156-160, 2014 | 3 | 2014 |
| An effective brain connectivity technique to predict repetitive transcranial magnetic stimulation outcome for major depressive disorder patients using EEG signals B Nobakhsh, A Shalbaf, R Rostami, R Kazemi, E Rezaei, R Shalbaf Physical and Engineering Sciences in Medicine 46 (1), 67-81, 2023 | 2 | 2023 |
| Combined yoga and transcranial direct current stimulation increase functional connectivity and synchronization in the frontal areas O Sefat, MA Salehinejad, M Danilewitz, R Shalbaf, F Vila-Rodriguez Brain Topography 35 (2), 207-218, 2022 | 2 | 2022 |
| Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal SM Mirjebreili, R Shalbaf, A Shalbaf Physical and Engineering Sciences in Medicine, 1-10, 2024 | 1 | 2024 |
Hamid BehnamSchool of Electrical Engineering, Iran University of Science and TechnologyBestätigte E-Mail-Adresse bei iust.ac.ir
