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  Citation statistics : Table of Contents
   2018| October-December  | Volume 8 | Issue 4  
    Online since September 13, 2019

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Claustrophobia game: Design and development of a new virtual reality game for treatment of claustrophobia
Vida Kabiri Rahani, Alireza Vard, Mostafa Najafi
October-December 2018, 8(4):231-237
DOI:10.4103/jmss.JMSS_27_18  PMID:30603615
Background: Claustrophobia or fear of closed spaces is the most common of phobias that is typically categorized as an anxiety disorder. Different methods have been proposed for treatment of phobias that one of the most recent and successful of these methods is applying virtual reality (VR) technology and simulating computer-generated environment. In this regard, the purpose of this research is design and development of a software game called “Claustrophobia Game” for treatment of claustrophobia using VR. Methods: In the Claustrophobia Game project, two closed spaces, including an elevator and a magnetic resonance imaging (MRI) device, were designed and implemented in the form of a VR computer game. To design this game, environments and scenario of the game were prepared in collaboration with a psychiatrist expert. Implementation of the software game was developed in the unity three-dimensional (3D) game engine and the programming of it was done by the C# language. In addition, a personal computer and the Oculus Rift VR glasses were utilized for running and testing the Claustrophobia Game. Results: To evaluate, we tested the game by 33 participants (14 men, 19 women, average age 24.6 years). In this regard, the Claustrophobia Game was considered from two aspects: psychology and playability using two questionnaires. Statistical analysis of the obtained data by the Excel software showed that all playability factors were “good” performance. In addition, the mean of obvious anxiety was decreased after playing the game. Conclusion: The promising results demonstrate that the game has an appropriate performance and can help to treat the Claustrophobia.
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Design and construction of a laser-based respiratory gating system for implementation of deep inspiration breathe hold technique in radiotherapy clinics
Mohammad Javad Keikhai Farzaneh, Shahrokh Nasseri, Mehdi Momennezhad, Roham Salek
October-December 2018, 8(4):253-262
DOI:10.4103/jmss.JMSS_35_18  PMID:30603618
Background: Deep inspiration breath-hold (DIBH) is known as a radiotherapy method for the treatment of patients with left-sided breast cancer. In this method, patient is under exposure only while he/she is at the end of a deep inspiration cycle and holds his/her breath. In this situation, the volume of the lung tissue is enhanced and the heart tissue is pushed away from the treating breast. Therefore, heart dose of these patients, using DIBH, experiences a considerable decline compared to free breathing treatment. There are a few commercialized systems for implementation of DIBH in invasive or noninvasive manners. Methods: We present a novel constructed noninvasive DIBH device relied on a manufacturing near-field laser distance meter. This in-house constructed system is composed of a CD22-100AM122 laser sensor combined with a data acquisition system for monitoring the breathing curve. Qt Creator (a cross-platform JavaScript, QML, and C++-integrated development environment that is part of the SDK for development of the Qt Graphical User Interface application framework) and Keil MDK-ARM (a programming software where users can write in C and C++ and assemble for ARM-based microcontrollers) are used for composing computer and microcontroller programs, respectively. Results: This system could be mounted in treatment or computed tomography (CT) room at suitable cost; it is also easy to use and needs a little training for personnel and patients. The system can assess the location of chest wall or abdomen in real time with high precision and frequency. The performance of CD22-100AM122 demonstrates promise for respiratory monitoring for its fast sampling rate as well as high precision. It can also deliver reasonable spatial and temporal accuracy. The patient observes his/her breathing waveform through a 7” 1024 × 600 liquid crystal display and gets some instructions during treatment and CT sessions by an exploited algorithm called “interaction scenario” in this study. The system is also noninvasive and well sustainable for patients. Conclusions: The constructed system has true real-time operation and is rapid enough for delivering clear contiguous monitoring. In addition, in this system, we have provided an interaction scenario option between patient and CT or Linac operator. In addition, the constructed system has the capability of sending triggers for turning on and off CT or Linac facilities. In this concern, the system has the superiority of combining a plenty of characteristics.
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The empirical mode decomposition-decision tree method to recognize the steady-state visual evoked potentials with wide frequency range
Sahar Sadeghi, Ali Maleki
October-December 2018, 8(4):225-230
DOI:10.4103/jmss.JMSS_20_18  PMID:30603614
Background: The empirical mode decomposition (EMD) is a technique to analyze the steady-state visual evoked potential (SSVEP) which decomposes the signal into its intrinsic mode functions (IMFs). Although for the limited stimulation frequency range, choosing the effective IMF leads to good results, but extending this range will seriously challenge the method so that even the combination of IMFs is associated with error. Methods: Stimulation frequencies ranged from 6 to 16 Hz with an interval of 0.5 Hz were generated using Psychophysics toolbox of MATLAB. SSVEP signal was recorded from six subjects. The EMD was used to extract the effective IMFs. Two features, including the frequency related to the peak of spectrum and normalized local energy in this frequency, were extracted for each of six conditions (each IMF, the combination of two consecutive IMFs and the combination of all three IMFs). Results: The instantaneous frequency histogram and the recognition accuracy diagram indicate that for wide stimulation frequency range, not only one IMF, but also the combination of IMFs does not have desirable efficiency. Total recognition accuracy of the proposed method was 79.75%, while the highest results obtained from the EMD-fast Fourier transform (FFT) and the CCA were 72.05% and 77.31%, respectively. Conclusion: The proposed method has improved the recognition rate more than 2.4% and 7.7% compared to the CCA and EMD-FFT, respectively, by providing the solution for situations with wide stimulation frequency range.
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A new method for detecting P300 signals by using deep learning: Hyperparameter tuning in high-dimensional space by minimizing nonconvex error function
Seyed Vahab Shojaedini, Sajedeh Morabbi, MohammadReza Keyvanpour
October-December 2018, 8(4):205-214
DOI:10.4103/jmss.JMSS_7_18  PMID:30603612
Background: P300 signal detection is an essential problem in many fields of Brain-Computer Interface (BCI) systems. Although deep neural networks have almost ubiquitously used in P300 detection, in such networks, increasing the number of dimensions leads to growth ratio of saddle points to local minimums. This phenomenon results in slow convergence in deep neural network. Hyperparameter tuning is one of the approaches in deep learning, which leads to fast convergence because of its ability to find better local minimums. In this paper, a new adaptive hyperparameter tuning method is proposed to improve training of Convolutional Neural Networks (CNNs). Methods: The aim of this paper is to introduce a novel method to improve the performance of deep neural networks in P300 signal detection. To reach this purpose, the proposed method transferred the non-convex error function of CNN) into Lagranging paradigm, then, Newton and dual active set techniques are utilized for hyperparameter tuning in order to minimize error of objective function in high dimensional space of CNN. Results: The proposed method was implemented on MATLAB 2017 package and its performance was evaluated on dataset of Ecole Polytechnique Fédérale de Lausanne (EPFL) BCI group. The obtained results depicted that the proposed method detected the P300 signals with 95.34% classification accuracy in parallel with high True Positive Rate (i.e., 92.9%) and low False Positive Rate (i.e., 0.77%). Conclusions: To estimate the performance of the proposed method, the achieved results were compared with the results of Naive Hyperparameter (NHP) tuning method. The comparisons depicted the superiority of the proposed method against its alternative, in such way that the best accuracy by using the proposed method was 6.44%, better than the accuracy of the alternative method.
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Annual congress of the school of advanced technologies in medicine, 2018
Maryam Samieinasab, Zahra Amini
October-December 2018, 8(4):263-264
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An efficient asynchronous high-frequency steady-state visual evoked potential-based brain-computer interface speller: The problem of individual differences
Saba Ajami, Amin Mahnam, Samane Behtaj, Vahid Abootalebi
October-December 2018, 8(4):215-224
DOI:10.4103/jmss.JMSS_19_18  PMID:30603613
Background: Brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs) provide high rates of accuracy and information transfer rate, but need user's attention to flickering visual stimuli. This quickly leads to eye-fatigue when the flickering frequency is in the low-frequency range. High-frequency flickering stimuli (>30 Hz) have been proposed with significantly lower eye-fatigue. However, SSVEP responses in this frequency range are remarkably weaker, leading to doubts about usability of high-frequency stimuli to develop efficient BCI systems. The purpose of this study was to evaluate if a practical SSVEP Speller can be developed with Repetitive Visual Stimuli in the high-frequency range. Methods: An asynchronous high-frequency (35–40 Hz) speller for typing in Persian language was developed using five flickering visual stimuli. Least absolute shrinkage and selection operator algorithm with two user-calibrated thresholds was used to detect the user's selections. A total of 14 volunteers evaluated the system in an ordinary office environment to type 9 sentences consist of 81 characters with a multistage virtual keyboard. Results: Despite very high performance of 6.9 chars/min overall typing speed, average accuracy of 98.3%, and information transfer rate of 64.9 bpm for eight of the participants, the other six participants had serious difficulty in spelling with the system and could not complete the typing experiment. Conclusions: The results of this study in accordance with some previous studies suggest that high rate of illiteracy in high-frequency SSVEP-based BCI systems may be a major burden for their practical application.
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Estimation of the thyroid secondary cancer risk on the patient of standard breast external beam radiotherapy
Zeinab Momeni, Mohammad Bagher Tavakoli, Maryam Atarod
October-December 2018, 8(4):238-243
DOI:10.4103/jmss.JMSS_12_18  PMID:30603616
Background: The purpose of this study was to estimate the secondary cancer risk of thyroid in standard radiotherapy methods which are commonly used for breast cancer patients. Methods: A total of 64 breast cancer patients (their age range was around 50 years old) who referred to Seyed-Al-Shohada hospital (Isfahan, Iran) were included in this study. The radiotherapy of the mentioned patients was performed using 6-MV photon beams. Dose measurements were also done using thermoluminescent dosimeters. Calculation of the risk of developing secondary cancer in thyroid was done using the Biological Effects of Ionizing Radiation Committee VII and recommended quantity of the International Radiation Protection Commission, excess relative risk. Results: The mean radiation dose to thyroid for the tangential beams, tangential field with supraclavicular (SC) field, and also a tangential field with SC field in modified radical mastectomy (MRM) were 0.883 ± 0.472, 1.512 ± 0.365, and 1.587 ± 0.37, respectively. The risk of developing secondary thyroid cancer over a period of 5 years after breast cancer therapy in the tangential, tangential with a SC field, and also tangential beam with SC field in MRM were 9.974 ± 4.318, 17.891 ± 0.365, and 18.783 ± 4.384, respectively. The mean of the measured thyroid doses in patients treated with tangent fields was significantly lower than the patients under the irradiation of the tangent fields with SC field (P < 0.001). Conclusions: Using radiation protection equipment is suggested for breast cancer patients who treated with the studied radiotherapy methods.
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Noninvasive quantification of liver fat content by different gradient echo magnetic resonance imaging sequences in patients with nonalcoholic fatty liver disease
Mansour Zabihzadeh, Mohammad Momen Gharibvand, Azim Motamedfar, Morteza Tahmasebi, Amir Hossein Sina, Kavous Bahrami, Mozafar Naserpour
October-December 2018, 8(4):244-252
DOI:10.4103/jmss.JMSS_32_18  PMID:30603617
Background: Noninvasive quantification of liver fat by gradient echo (GRE) technique is an interesting issue in quantitative magnetic resonance imaging. In this study, the fat content in patients with nonalcoholic fatty liver disease (NAFLD) was quantified with GRE sequences with different T1 and T2*weighting. Methods: This prospective, cross-sectional study was performed on thirty NAFLD patients. Sixteen GRE sequences with different T1weighting were performed with four echo times. In each sequence, repetition time (TR) or flip angle was changed and other parameters were fixed. Forty-eight fat indexes (FIs) from 16 sequences were calculated based on three methods. To determine the relationship between FIs and histological findings, Pearson's correlation coefficient was used at the level of 1% significance. Results: Mean FIs which obtained from Eq. 3 have the maximum values in comparison to other FIs. The maximum FI was 23.58%, which related to heavily T1weighted sequence obtained with method 3. The minimum FI was −2.49%, which related to the minimal T1weighted obtained with method 2. FIs increase with a flip angle, especially at low flip angles. Increase the TR parameter decrease the FIs gradually. Calculated FIs with methods 1 and 3 stronger correlated with histological findings relative to calculated FIs with method 2. Conclusion: For fat quantification, T1relaxation effects probably more critical than T2*. Flip angle parameter could be a major factor causing the overestimation of liver fat content. Sequences with low flip angle are more suitable for fat quantification with methods 1 and 3. In fat quantification with GRE techniques, it is possible that the third and fourth echoes are unnecessary.
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