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electrophysiology
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Sequential nonlinear encoding: A low dimensional regression algorithm with application to EEG-based driving fatigue detection
, Article Scientia Iranica ; Volume 29, Issue 3 , 2022 , Pages 1486-1505 ; 10263098 (ISSN) ; Mohammadzade, H ; Sharif University of Technology
Sharif University of Technology
2022
Abstract
Regression analysis of real-world data has not always been an easy task, especially when input vectors are presented in a very low dimensional space. EEG-based fatigue detection deals with low dimensional problems and plays a major role in reducing the risk of fatal accidents. We propose a kernel projection pursuit regression algorithm which is a two-step nonlinearity encoding algorithm tailored for such low dimensional problems such as fatigue detection. In this way, data nonlinearity can be investigated from two different perspectives: by first transforming the data into a high dimensional intermediate space and then, applying their spline estimations to the output variables allowing for...
Wavelet-Based biphase analysis of brain rhythms in automated wake-sleep classification
, Article International Journal of Neural Systems ; 2022 ; 01290657 (ISSN) ; Makkiabadi, B ; Shamsollahi, M. B ; Reisi, P ; Kermani, S ; Sharif University of Technology
World Scientific
2022
Abstract
Many studies in the field of sleep have focused on connectivity and coherence. Still, the nonstationary nature of electroencephalography (EEG) makes many of the previous methods unsuitable for automatic sleep detection. Time-frequency representations and high-order spectra are applied to nonstationary signal analysis and nonlinearity investigation, respectively. Therefore, combining wavelet and bispectrum, wavelet-based bi-phase (Wbiph) was proposed and used as a novel feature for sleep-wake classification. The results of the statistical analysis with emphasis on the importance of the gamma rhythm in sleep detection show that the Wbiph is more potent than coherence in the wake-sleep...
Mechanical properties of ester- and ether-DPhPC bilayers: A molecular dynamics study
, Article Journal of the Mechanical Behavior of Biomedical Materials ; Volume 117 , 2021 ; 17516161 (ISSN) ; Jamali, Y ; Tajkhorshid, E ; Bavi, O ; Pishkenari, H. N ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
In addition to its biological importance, DPhPC lipid bilayers are widely used in droplet bilayers, study of integral membrane proteins, drug delivery systems as well as patch-clamp electrophysiology of ion channels, yet their mechanical properties are not fully measured. Herein, we examined the effect of the ether linkage on the mechanical properties of ester- and ether-DPhPC lipid bilayers using all-atom molecular dynamics simulation. The values of area per lipid, thickness, intrinsic lateral pressure profile, order parameter, and elasticity moduli were estimated using various computational frameworks and were compared with available experimental values. Overall, a good agreement was...
Combined effects of electric stimulation and microgrooves in cardiac tissue-on-a-chip for drug screening
, Article Small Methods ; Volume 4, Issue 10 , 2020 ; Zhou, X ; Nasiri, R ; Fang, J ; Jiang, X ; Wang, C ; Qu, M ; Ling, H ; Chen, Y ; Xue, Y ; Hartel, M.C ; Tebon, P ; Zhang, S ; Kim, H.-J ; Yuan, X ; Shamloo, A ; Dokmeci, M. R ; Li, S ; Khademhosseini, A ; Ahadian, S ; Sun, W ; Sharif University of Technology
John Wiley and Sons Inc
2020
Abstract
Animal models and traditional cell cultures are essential tools for drug development. However, these platforms can show striking discrepancies in efficacy and side effects when compared to human trials. These differences can lengthen the drug development process and even lead to drug withdrawal from the market. The establishment of preclinical drug screening platforms that have higher relevancy to physiological conditions is desirable to facilitate drug development. Here, a heart-on-a-chip platform, incorporating microgrooves and electrical pulse stimulations to recapitulate the well-aligned structure and synchronous beating of cardiomyocytes (CMs) for drug screening, is reported. Each chip...
Online analysis of local field potentials for seizure detection in freely moving rats
, Article Iranian Journal of Basic Medical Sciences ; Volume 23, Issue 2 , 2020 , Pages 173-177 ; Nazari, M ; Shojaei, A ; Raoufy, M. R ; Mirnajafi Zadeh, J ; Sharif University of Technology
Mashhad University of Medical Sciences
2020
Abstract
Objective(s): Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Materials and Methods: Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Results: Obtained results showed that changes in LFP power...
A generalizable model for seizure prediction based on deep learning using CNN-LSTM architecture
, Article 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018, 26 November 2018 through 29 November 2018 ; 2019 , Pages 469-473 ; 9781728112954 (ISBN) ; Aghajan, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
This work proposes a novel deep learning-based model for prediction of epileptic seizures using multichannel EEG signals. Multichannel images are first constructed by applying short-time Fourier transform (STFT) to Electroencephalography (EEG) signals. After a preprocessing step, a CNN-LSTM neural network is trained on the STFTs in order to capture the spectral, spatial and temporal features within and between the EEG segments and classify them as preictal or interictal stage. The proposed method achieves a sensitivity of 98.21%, a false prediction rate (FPR) of 0.13/h and a mean prediction time of 44.74 minutes on the CHB-MIT dataset. As the main contribution of this work, by using a...
The effect of different light intensities and light/dark regimes on the performance of photosynthetic microalgae microbial fuel cell
, Article Bioresource Technology ; Volume 261 , 2018 , Pages 350-360 ; 09608524 (ISSN) ; Roshandel, R ; Yaghmaei, S ; Mardanpour, M. M ; Sharif University of Technology
Elsevier Ltd
2018
Abstract
This study develops a photosynthetic microalgae microbial fuel cell (PMMFC) engaged Chlorella vulgaris microalgae to investigate effect of light intensities and illumination regimes on simultaneous production of bioelectricity, biomass and wastewater treatment. The performance of the system under different light intensity (3500, 5000, 7000 and 10,000 lx) and light/dark regimes (24/00, 12/12, 16/8 h) was investigated. The optimum light intensity and light/dark regimes for achieving maximum yield of PMMFC were obtained. The maximum power density of 126 mW m−3, the coulombic efficiency of 78% and COD removal of 5.47% were achieved. The maximum biomass concentration of 4 g l−1 (or biomass yield...
Characteristics of early repolarization pattern in the Iranian population
, Article Iranian Red Crescent Medical Journal ; Volume 19, Issue 3 , 2017 ; 20741804 (ISSN) ; Sehhati, F ; Eslami, M ; Nemati, F ; Monfarednasab, M ; Sefidbakht, S ; Sharif University of Technology
Kowsar Medical Publishing Company
2017
Abstract
Background: The early repolarization pattern (ERP) has been considered a normal variant in electrocardiography (ECG) for a long time. Nevertheless, increasing evidence has demonstrated its association with adverse outcomes. Objectives: The present study aimed to evaluate the prevalence of ERP in the Iranian general population and demonstrate its clinical and ECG correlates. Methods: A cross sectional study, comprising 1424 consecutive healthy adult individuals, was conducted at two university based hospitals in Tehran, Iran in 2012-2013. The ERP prevalence, clinical characteristics and ECG morphology were investigated in volunteers. Results: ERP was present in 136 out of 1,424 people (9.6%)....
Modeling of microfluidic microbial fuel cells using quantitative bacterial transport parameters
, Article Journal of Power Sources ; Volume 342 , 2017 , Pages 1017-1031 ; 03787753 (ISSN) ; Yaghmaei, S ; Kalantar, M ; Sharif University of Technology
Elsevier B.V
2017
Abstract
The objective of present study is to analyze the dynamic modeling of bioelectrochemical processes and improvement of the performance of previous models using quantitative data of bacterial transport parameters. The main deficiency of previous MFC models concerning spatial distribution of biocatalysts is an assumption of initial distribution of attached/suspended bacteria on electrode or in anolyte bulk which is the foundation for biofilm formation. In order to modify this imperfection, the quantification of chemotactic motility to understand the mechanisms of the suspended microorganisms’ distribution in anolyte and/or their attachment to anode surface to extend the biofilm is implemented...
Characterization of a microfluidic microbial fuel cell as a power generator based on a nickel electrode
, Article Biosensors and Bioelectronics ; Volume 79 , 2016 , Pages 327-333 ; 09565663 (ISSN) ; Yaghmaei, S ; Sharif University of Technology
Elsevier Ltd
2016
Abstract
This study reports the fabrication of a microfluidic microbial fuel cell (MFC) using nickel as a novel alternative for conventional electrodes and a non-phatogenic strain of Escherichia coli as the biocatalyst. The feasibility of a microfluidic MFC as an efficient power generator for production of bioelectricity from glucose and urea as organic substrates in human blood and urine for implantable medical devices (IMDs) was investigated. A maximum open circuit potential of 459mV was achieved for the batch-fed microfluidic MFC. During continuous mode operation, a maximum power density of 104Wm-3 was obtained with nutrient broth. For the glucose-fed microfluidic MFC, the maximum power density of...
One-dimensional Conduction-based Modeling of Bioenergy Production in a Microbial Fuel Cell Engaged with Multi-population Biocatalysts
, Article Electrochimica Acta ; Volume 184 , December , 2015 , Pages 151-163 ; 00134686 (ISSN) ; Mardanpour, M. M ; Yaghmaei, S ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
Anaerobic digestion processes and the conductive electron transfer approach were used to describe the bioenergy production processes in a microbial fuel cell (MFC), respectively. The present model is a far more completed form of conduction-based modeling which is able to predict performance of an MFC fed with complex substrates and inoculated with multi-population culture. One-dimensional spatial distributions of the different microorganisms, as biocatalysts of processes and intermediates produced in the different steps of the anaerobic digestion processes in the biofilm, as well as the dynamic behavior of the anolyte including syntropic interactions among different groups of microorganisms...
Toward epileptic brain region detection based on magnetic nanoparticle patterning
, Article Sensors (Switzerland) ; Volume 15, Issue 9 , September , 2015 , Pages 24409-24427 ; 14248220 (ISSN) ; Shamloo, A ; Alasty, A ; Ghafar Zadeh, E ; Sharif University of Technology
MDPI AG
2015
Abstract
Resection of the epilepsy foci is the best treatment for more than 15% of epileptic patients or 50% of patients who are refractory to all forms of medical treatment. Accurate mapping of the locations of epileptic neuronal networks can result in the complete resection of epileptic foci. Even though currently electroencephalography is the best technique for mapping the epileptic focus, it cannot define the boundary of epilepsy that accurately. Herein we put forward a new accurate brain mapping technique using superparamagnetic nanoparticles (SPMNs). The main hypothesis in this new approach is the creation of super-paramagnetic aggregates in the epileptic foci due to high electrical and...
An efficient Jacobi-like Deflationary ICA algorithm: Application to EEG denoising
, Article IEEE Signal Processing Letters ; Volume 22, Issue 8 , December , 2015 , Pages 1198-1202 ; 10709908 (ISSN) ; Albera, L ; Shamsollahi, M. B ; Merlet, I ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
In this paper, we propose a Jacobi-like Deflationary ICA algorithm, named JDICA. More particularly, while a projection-based deflation scheme inspired by Delfosse and Loubaton's ICA technique (DelLR) is used, a Jacobi-like optimization strategy is proposed in order to maximize a fourth order cumulant-based contrast built from whitened observations. Experimental results obtained from simulated epileptic EEG data mixed with a real muscular activity and from the comparison in terms of performance and numerical complexity with the FastICA, RobustICA and DelLR algorithms, show that the proposed algorithm offers the best trade-off between performance and numerical complexity when a low number (∼...
EEG-based functional brain networks: Hemispheric differences in males and females
, Article Networks and Heterogeneous Media ; Volume 10, Issue 1 , March , 2015 , Pages 223-232 ; 15561801 (ISSN) ; Sharif University of Technology
American Institute of Mathematical Sciences
2015
Abstract
Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks whose nodes are brain regions and edges correspond to functional links between them are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using...
Bioelectricity Generation in a Soil Microbial Fuel Cell with Biocathode Denitrification
, Article ; Volume 37, Issue 19 , 2015 , Pages 2092-2098 ; 15567036 (ISSN) ; Roshandel, R ; Yaghmaei, S ; Vajihinejad, V ; Sherafatmand, M ; Sharif University of Technology
Taylor and Francis Inc
2015
Abstract
A soil microbial fuel cell was investigated that uses soil and groundwater to generate electricity. The cathode surface area and materials are always important for increasing power. Power density was shown to be a linear function of cathode surface area. Biofilm formation on the graphite cathode was observed to be helpful in enhancing power output and maximum performance reached 89.2 mW/m2. As an application for the insertion-type soil microbial fuel cell, nitrate removing was investigated in cathode. Nitrate was reduced in an aerobic cathode at the rate of 37.5 mg nitrate/lit/day and 55 mg nitrate/lit/day in anaerobic cathode
Neural implant stimulation based on TiO2 nanostructured arrays; A multiphysics modeling verification
, Article IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet", 8 December 2014 through 10 December 2014 ; December , 2015 , Pages 677-680 ; 9781479940844 (ISBN) ; Mohammadpour, R ; Amiri, K ; Silterra; University of Malaya ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
Exploiting of the nanostructure arrays as a promising candidate for excitation of neural cells has been analyzed. Based on the importance of the coupling effect between electrode and neuron, a multiphyscis modeling approach has been proposed. The model incorporates theoretically both structural effects (size, geometry) and electrophysiological effects. The system of equations for proposed model has been solved numerically using Finite Element Method for Poisson equation and Finite Difference Method for Cable equation. In this regards we have combined the system of equations in COMSOL platform with Matlab interface accordingly. We have analyzed the effect of excitation of neuron with an extra...
Diagnosis of early Alzheimer's disease based on EEG source localization and a standardized realistic head model
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 17, Issue 6 , 2013 , Pages 1039-1045 ; 21682194 (ISSN) ; Zahedi, E ; Jalili, M ; Keikhosravi, A ; Vahdat, B. V ; Sharif University of Technology
2013
Abstract
In this paper, distributed electroencephalographic (EEG) sources in the brain have been mapped with the objective of early diagnosis of Alzheimer's disease (AD). To this end, records from a montage of a high-density EEG from 17 early AD patients and 17 matched healthy control subjects were considered. Subjects were in eyes-closed, resting-state condition. Cortical EEG sources were modeled by the standardized low-resolution brain electromagnetic tomography (sLORETA) method. Relative logarithmic power spectral density values were obtained in the four conventional frequency bands (alpha, beta, delta, and theta) and 12 cortical regions. Results show that in the left brain hemisphere, the theta...
Multivariate Synchronization Analysis of Brain Electroencephalography Signals: A Review of Two Methods
, Article Cognitive Computation ; Volume 7, Issue 1 , February , 2013 , Pages 3-10 ; 18669956 (ISSN) ; Sharif University of Technology
Springer New York LLC
2013
Abstract
Temporal synchronization of neuronal activity plays an important role in various brain functions such as binding, cognition, information processing, and computation. Patients suffering from disorders such as Alzheimer’s disease or schizophrenia show abnormality in the synchronization patterns. Electroencephalography (EEG) is a cheap, non-invasive, and easy-to-use method with fine temporal resolution. Modern multichannel EEG data are increasingly being used in brain studies. Traditional approaches for identifying synchronous activity in EEG are through univariate techniques such as power spectral density or bivariate techniques such as coherence. In this paper, we review two methods for...
Bimodal electricity generation and aromatic compounds removal from purified terephthalic acid plant wastewater in a microbial fuel cell
, Article Biotechnology Letters ; Volume 35, Issue 2 , 2013 , Pages 197-203 ; 01415492 (ISSN) ; Kariminia, H. R ; Savizi, I. S. P ; Sharif University of Technology
2013
Abstract
Wastewater of purified terephthalic acid (PTA) from a petrochemical plant was examined in a membrane-less single chamber microbial fuel cell for the first time. Time course of voltage during the cell operation cycle had two steady phases, which refers to the fact that metabolism of microorganisms was shifted from highly to less biodegradable carbon sources. The produced power density was 31.8 mW m-2 (normalized per cathode area) and the calculated coulombic efficiency was 2.05 % for a COD removal of 74 % during 21 days. The total removal rate of different pollutants in the PTA wastewater was observed in the following order: (acetic acid) > (benzoic acid) > (phthalic acid) > (terephthalic...
Noise cancelation of epileptic interictal EEG data based on generalized eigenvalue decomposition
, Article 2012 35th International Conference on Telecommunications and Signal Processing, TSP 2012 - Proceedings ; 2012 , Pages 591-595 ; 9781467311182 (ISBN) ; Shamsollahi, M. B ; Albera, L ; Merlet, I ; Sharif University of Technology
2012
Abstract
Denoising is an important preprocessing stage in some Electroencephalography (EEG) applications such as epileptic source localization. In this paper, we propose a new algorithm for denoising the interictal EEG data. The proposed algorithm is based on Generalized Eigenvalue Decomposition of two covariance matrices of the observations. Since one of these matrices is related to the spike durations, we should estimate the occurrence time of the spike peaks and the exact spike durations. To this end, we propose a spike detection algorithm which is based on the available spike detection methods. The comparison of the results of the proposed algorithm with the results of two well-known ICA...