فهرست مطالب

Medical Signals and Sensors - Volume:6 Issue: 4, 2016
  • Volume:6 Issue: 4, 2016
  • تاریخ انتشار: 1395/08/04
  • تعداد عناوین: 8
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  • Hossein Rabbani Page 195
    The current curriculum for both medical and engineering students does not include any serious program for research and technology development, by which capable students can become a man of research and a man with high-tech skills as soon as possible. However, there are opportunities for several good experiences in Iranian universities such as “Research Student Clubs,” [2,3] which show that there exists a huge potential for the student to learn and do research.
  • Ali Pourahmad, Amin Mahnam* Page 197
    Wet Ag/AgCl electrodes, although very popular in clinical diagnosis, are not appropriate for expanding applications of wearable biopotential recording systems which are used repetitively and for a long time. Here, the development of a low‑cost and low‑noise active dry electrode is presented. The performance of the new electrodes was assessed for recording electrocardiogram (ECG) and electroencephalogram (EEG) in comparison with that of typical gel‑based electrodes in a series of long‑term recording experiments. The ECG signal recorded by these electrodes was well comparable with usual Ag/AgCl electrodes with a correlation up to 99.5% and mean power line noise below 6.0 µVRMS. The active electrodes were also used to measure alpha wave and steady state visual evoked potential by recording EEG. The recorded signals were comparable in quality with signals recorded by standard gel electrodes, suggesting that the designed electrodes can be employed in EEG‑based rehabilitation systems and brain‑computer interface applications. The mean power line noise in EEG signals recorded by the active electrodes (1.3 µVRMS) was statistically lower than when conventional gold cup electrodes were used (2.0 µVRMS) with a significant level of 0.05, and the new electrodes appeared to be more resistant to the electromagnetic interferences. These results suggest that the developed low‑cost electrodes can be used to develop wearable monitoring systems for long‑term biopotential recording.
    Keywords: Brain, electrocardiography, electrodes, electroencephalography, electromagnetic phenomena, evoked potentials
  • Nasrin Shourie* Page 203
    In this article, multichannel EEG signals of artists and nonartists were analyzed during the performances of visual perception and mental imagery of paintings using cepstrum coefficients. Each of the calculated cepstrum coefficients and their parameters such as energy, average, standard deviation and entropy were separately used for distinguishing the two groups. It was also found that a distinguishing coefficient might exist among the cepstrum coefficients, which could separate the two groups despite electrode placement. It was also observed that the two groups were distinguishable during the three states using the cepstrum coefficient parameters. However, separating the two groups was dependent on channel selection in this regard. The cepstrum coefficient parameters were found significantly lower for artists as compared to nonartists during the visual perception and the mental imagery, indicating a decreased average energy of EEG for artists. In addition, a similar significant decreasing trend in the cepstrum coefficient parameters was observed from occipital to frontal brain regions during the performances of the two cognitive tasks for the two groups, suggesting that visual perception and its mental imagery overlap in neuronal resources. The two groups were also classified using a neural gas classifier and a support vector machine classifier. The obtained average classification accuracies during the visual perception, the mental imagery, and at rest in the case of using the best selected distinguishable cepstrum coefficients were 76.87%, 77.5%, and 97.5%, respectively; however, a decrease in average recognition accuracy was found for classifying the two groups using the cepstrum coefficient parameters.
    Keywords: Brain, cognition, electrodes, electroencephalography, entropy, paintings, support vector machine, visual perception
  • Mohammad Pooyan*, Fateme Akhoondi Page 218
    Ventricular arrhythmias are one of the most important causes of annual deaths in the world, which may lead to sudden cardiac deaths. Accurate and early diagnosis of ventricular arrhythmias in heart diseases is essential for preventing mortality in cardiac patients. Ventricular activity on the electrocardiogram (ECG) signal is in the interval from the beginning of QRS complex to T wave end. Variations in the ECG signal and its features may indicate heart condition of patients. The first step to extract features of ECG in time domain is finding R peaks. In this paper, a combination of two algorithms of Pan–Tompkins and state logic machine has been used to find R peaks in heart signals for normal sinus signals and ventricular abnormalities. Then, a healthy or sick beat may be realized by comparing the difference between R peaks obtained from two algorithms in each beat. The morphological features of the ECG signal in the range of QRS complex are evaluated. Ventricular tachycardia (VT), ventricular flutter (VFL), ventricular fibrillation (VFI), ventricular escape beat (VEB), and premature ventricular contractions (PVCs) are abnormalities studied in this paper. In the classification step, the support vector machine (SVM) classifier with Gaussian kernel (one in front of everyone) is used. Accuracy percentages of ventricular abnormalities mentioned above and normal sinus rhythm are respectively obtained as 95.8%, 92.8%, 94.5, 98.9%, 91.5%, and 100%. The database of this paper has been taken from normal sinus rhythm and MIT-SCD banks available on Physionet.org.
    Keywords: Electrocardiography, heart conduction system, humans, Pan–Tompkins algorithm, state logic machine, support vector machine, ventricular flutter, ventricular premature complexes
  • Fereshte Eradi Zare, Keivan Maghooli* Page 224
    Since gait is the mixture of many complex movements, each individual can define with a unique footpressure image that can be used as a reliable biometric scale for human verification. Foot pressure colorimages of Center for Biometrics and Security Research (CBSR) dataset from 45 men and five womenwere used in this study. Owing to the properties of this dataset, an index of foot pressure in addition toexternal feature and contourlet coefficient of images was extracted. A multilayer perceptron (MLP) wasutilized for verification of subjects (it is a common practice to explain more about the training and testdataset). To validate the algorithm performance, results were obtained using a 5-fold cross validationapproach.The results indicated accuracy of 99.14 ± 0.65 and equal error rate (EER) of 0.02. Theseresults demonstrated the reliability of proposed neural network in human verification application. Hence,it can be utilized in other verification systems.
    Keywords: Algorithms, biometry, foot, gait, human verification, neural networks
  • Hossein Yousefi Banaem, Hossein Rabbani *, Peyman Adibi Page 231
    Barrett's mucosa is one of the most important diseases in upper gastrointestinal system that caused by gastroesophagus reflux. If left untreated, the disease will cause distal esophagus and gastric cardiaadenocarcinoma. The malignancy risk is very high in short segment Barrett’s mucosa. Therefore,lesion area segmentation can improve specialist decision for treatment. In this paper, we proposeda combined fuzzy method with active models for Barrett’s mucosa segmentation. In this study,we applied three methods for special area segmentation and determination. For whole disease areasegmentation, we applied the hybrid fuzzy based level set method (LSM). Morphological algorithmswere used for gastroesophageal junction determination, and we discriminated Barrett’s mucosa from breakby applying Chan-Vase method. Fuzzy c-mean and LSMs fail to segment this type of medical imagedue to weak boundaries. In contrast, the full automatic hybrid method with correlation approachthat has used in this paper segmented the metaplasia area in the endoscopy image with desirableaccuracy. The presented approach omits the manually desired cluster selection step that needed theoperator manipulation. Obtained results convinced us that this approach is suitable for esophagusmetaplasia segmentation.
    Keywords: Adenocarcinoma, algorithms, Barrett's mucosa, cardia, endoscopy, esophagogastric junction, fuzzy logic, gastroesophageal reflux, metaplasia, segmentation
  • Mehdi Ebrahimian Hosseinabadi *, Mohammadreza Etemadifar, Fakhredin Ashrafizadeh Page 237
    In this paper, preparation, bioactivity, and osteoblast cell behavior of cortical bone derived nanobiphasic calcium phosphate (nano-BCP) are presented. The calcined bovine bone samples with the addition of di-ammonium hydrogen phosphate were heated at 700°C for 100 min, and thus nano-BCP with the composition of 63/37 hydroxyapatite (HA)/β-tricalcium phosphate (β-TCP) was produced. Scanning electron microscopy (SEM) images, energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) analysis of immersed samples in simulated body fluid (SBF) solution showed that a uniform layer was formed on the surface after 7 days with the chemical composition of HA. The results indicated that the nano-BCP sample developed excellent bioactivity after 28 days. The nano-BCP samples showed better cell proliferation compared to pure HA samples. After 7 days in cell culture, the prepared nano-BCP (HA/β-TCP) exhibited the maximum proliferation of the MG-63 osteoblast cells.
    Keywords: Animals, body fluids, calcium phosphates, cell proliferation, hydroxyapatites, osteoblasts, phosphates, spectrometry, X, Rays
  • Mohammad Keshtkar, Daryoush Shahbazi Gahrouei *, Masoud A. Mehrgardi, Mahmoud Aghaei Page 243
    Early detection of breast cancer is the most effective way to improve the survival rate in women. Magnetic resonance imaging (MRI) offers high spatial resolution and good anatomic details, and its lower sensitivity can be improved by using targeted molecular imaging. In this study, AS1411 aptamer was conjugated to Fe3O4@Au nanoparticles for specific targeting of 4T1 cells that overexpress nucleolin. In vitro cytotoxicity of aptamer-conjugated nanoparticles was assessed on 4T1 and HFFF-PI6 cells. The ability of the synthesized nanoprobe to target specifically the nucleolin overexpressed cells was assessed with the MRI technique. Results showed that the synthesized nanoprobe produced strongly darkened T2-weighted magnetic resonance (MR) images with 4T1 cells, whereas the MR images of HFFF-PI6 cells incubated with the nanoprobe were brighter, showing small changes compared to water. The results demonstrate that in a Fe concentration of 45 μg/mL, the nanoprobe reduced by 90% MR image intensity in 4T1 cells compared with the 27% reduction in HFFF-PI6 cells. Analysis of MR signal intensity showed statistically significant signal intensity difference between 4T1 and HFFF-PI6 cells treated with the nanoprobe. MRI experiments demonstrated the high potential of the synthesized nanoprobe as a specific MRI contrast agent for detection of nucleolin-expressing breast cancer cells.
    Keywords: Breast, contrast media, early detection of cancer, humans, magnetic resonance imaging, magnetic resonance spectroscopy, molecular imaging, nanoparticles, oligodeoxyribonucleotides, phosphoproteins, RNA, Binding proteins, survival rate