Volume 17 (2023)
Volume 16 (2022)
Volume 15 (2021)
Volume 14 (2020)
Volume 13 (2019)
Volume 12 (2018)
Volume 11 (2017)
Volume 10 (2016)
Volume 9 (2015)
Volume 8 (2014)
Volume 7 (2013)
Volume 6 (2012)
Volume 5 (2011)
Volume 4 (2010)
Volume 3 (2009)
Volume 2 (2008)
Volume 1 (2007)
Volume -2 (2005)
Volume -1 (2004)
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Arrhythmia Classification Improvement by Individually Mapping the Feature Space of each patient

Hamid Shafaatfar; Mehdi Taghizadeh; Morteza Valizadeh; Mohamad Hossein Fatehi

Volume 16, Issue 2 , September 2022, , Pages 147-158

  Automatic detection of cardiac arrhythmias is very important for the successful treatment of heart disease and machine learning is used for this purpose. To correctly classify arrhythmic classes, it is important to extract the appropriate features to distinguish between different classes. In this paper, ...  Read More

Feature Extraction for Object Recognition Inspired by Human Visual System

Hiwa Sufikarimi; Karim Mohammadi

Volume 11, Issue 4 , February 2018, , Pages 337-349

  In this paper, we tried to present a robust and reliable approach to object recognition by inspiring human visual system. A famous model, inspiring mammalian visual system, is HMAX (Hierarchical Model and X). It shows significant accuracy rates on object recognition tasks. However, there are some differences ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Brain Effective Connectivity Investigation With Directed Transform Function Method for Different Combination of Attention and Consciousness Based on EEG Signals

Masoumeh Rahimi; Mohammad Hasan Moradi; Farnaz Ghassemi

Volume 10, Issue 1 , May 2016, , Pages 59-68

  The aim of this paper is to study brain effective connectivity based on directed transform function (DTF) using granger causality method. This connectivity was calculated for recorded data in different states of attention and consciousness, forming four different classes: attention-consciousness, attention-unconsciousness, ...  Read More

Speech processing
Feature Extraction based on Linear Modeling of Embedded Speech Trajectory in the Reconstructed Phase Space for Speech Recognition System

Yaser Shekofteh; Farshad Almasganj

Volume 6, Issue 1 , June 2012, , Pages 17-33

  Recent researches show that nonlinear and chaotic behavior of the speech signal can be studied in the reconstructed phase space (RPS). Delay embedding theorem is a useful tool to study embedded speech trajectories in the RPS. Characteristics of the speech trajectories have rarely used in the practical ...  Read More

Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Assessment of Time, Frequency, and Wavelet Packet Transform Features Extracted from EEG for Sleep Staging using Self Organizing Maps (SOM)

Faride Ebrahimi; Mohammad Mikaili

Volume 4, Issue 2 , June 2010, , Pages 97-108

  Different biological signals including EEG, EOG, and EMG are recorded in sleep labs to diagnose sleep disorders. Data recorded during sleep is usually analyzed by sleep specialists visually. Since the sleep data is usually recorded for a long time period- namely a whole night- its visual inspection and ...  Read More

Development of P300 detection by Combination of Time, Frequency and Spatial Feature Extraction Methods

Zahra Amini; Vahid Abootalebi; Mohammad Taghi Sadeghi

Volume 4, Issue 4 , June 2010, , Pages 293-306

  The aim of this paper is to design a pattern recognition based system to detect P300 component in multi-channel electroencephalogram (EEG) trials. This system has two main blocks, feature extraction and classification. In feature extraction block, in addition to conventional features namely morphological, ...  Read More

An Experimental Investigation into the use of Ramanspectroscopy for the Diagnosis of Cancer

Zohre Dehghani Bidgoli; Mohammad Hossein Miranbaygi; Rasoul Malekfar; Ehsanollah Kabir; Tahere Khamechian

Volume 4, Issue 4 , June 2010, , Pages 307-316

  In this research, we investigated cancerous tissues from several organs of the human body using Raman spectroscopy. Different specimens with different pathologic labels (normal & cancerous) were borrowed from a pathology laboratory, and were investigated using two different Raman spectroscopy systems. ...  Read More

Biomedical Image Processing / Medical Image Processing
Alzheimer's Disease Diagnosis Using Nonlinear Weighted T1-Mri Classification

Meysam Torabi; Emadoddin Fatemizadeh

Volume 3, Issue 3 , June 2009, , Pages 213-225

  In this paper, an MRI-based diagnosing approach has been proposed which simultaneously analyzes T1-MR and T2-MR images. The dataset contains 120 cross-sectional images of abnormal and also normal brains as control group. Due to inherent proprieties of T1 and T2 images and their principal differences, ...  Read More