A Review on EEG Signals Based Emotion Recognition

Morteza Zangeneh Soroush, Keivan Maghooli, Seyed Kamaledin Setarehdan, Ali Motie Nasrabadi

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 118-129

Emotion recognition has become a very controversial issue in brain-computer interfaces (BCIs). Moreover, numerous studies have been conducted in order to recognize emotions. Also, there are several important definitions and theories about human emotions. In this paper we try to cover important topics related to the field of emotion recognition. We review several studies which are based on analyzing electroencephalogram (EEG) signals as a biological marker in emotion changes. Considering low cost, good time and spatial resolution, EEG has become very common and is widely used in most BCI applications and studies. First, we state some theories and basic definitions related to emotions. Then some important steps of an emotion recognition system like different kinds of biologic measurements (EEG, electrocardiogram [EEG], respiration rate, etc), offline vs online recognition methods, emotion stimulation types and common emotion models are described. Finally, the recent and most important studies are reviewed.

Evaluation of Depression and its Related Factors Among Female Students in Fasa, Iran

Farzaneh Modarresi, Farhood Nikouee, Amir Ansari, Mophsen Rezaee

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 130-133

Background: We aimed to determine frequency of depression among female adolescent students and its related factors in Fasa, Iran.
Methods: In a cross-sectional study, female high school students were evaluated. Depression, mental disorder and family’s relative peace were measured using standard scales.
Results: A total of 516 students were evaluated in which 157 (30.4%) students did not suffer any type of depression. The mean depression score of students had significant relationship with history of an addicted family member (P < 0.001), family relative peace (P < 0.001), history of any mental-psychological disorder in family (P < 0.001) and parents’ educational level (P = 0.03).
Conclusion: The prevalence of depression was high in female students and was associated with variables such as drug-addicted family member, relative peace and history of mental-psychological disorders in the family.

Detection of Focal Epileptic Seizure Using NIRS Signal Based on Discrete Wavelet Transform

Aslan Modir, Mohammad Ali Khalilzadeh, Ali Gorji

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 134-139

Background: Despite the large number of research and significant advances in neuroscience, the hemodynamic activities of epilepsy have been rarely investigated due to high costs, need for contrast agents in fMRI and PET, lack of signals during epileptic seizure and un-portability of the equipment. Recently, Near-infrared spectroscopy (NIRS) system has attracted a large number of researchers. This system does not have the above-mentioned problems and provides a better temporal resolution than the other equipment; however, it cannot be compared to PET or fMRI, in terms of spatial resolution. The project was conducted with a feasibility study to detect epileptic seizures and extraction of epileptic dynamics using a time multiplex system at 2 wavelengths of 740 and 850 nm. Analyzing the frequency and temporal-domains of 8 patients with focal epilepsy in temporal area during the time of sleeping, we can identify the most difference between epileptic and normal conditions in low-frequencies at the high order Daubechies wavelet transform of hemodynamic components. The main challenge is the significant resemblances between epileptic dynamic and motion artifact in low frequencies. Finally, using the most appropriate features such as Shannon entropy and the new index that we named “upgraded cumulants” showing proper separability under t test and also by using different classifiers, the best result was achieved with the help of SVM classifier with an accuracy of 78.57%

 

Comparison of the homodynamic effects of Nesdonal and Propofol in patients under electroconvulsive therapy

Afsoun Seddighi, Amir Nikouei, Amir Saied Seddighi

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 140-142

Background: General anesthesia is a safe method for induction of electroconvulsive therapy (ECT) in patients suffering from psychiatric disorders. We aimed to compare the hemodynamic effects of Nesdonal and propofol as induction agents for ECT.
Methods: This semi-experimental study was performed on 84 patients with confirmed diagnosis of psychiatric disorders, who underwent ECT at Shohada Tajrish hospital in 2016. After randomization, each patient either received Nesdonal or propofol for induction of anesthesia. Hemodynamic changes of mentioned anesthetic agents were recorded and evaluated during ECT, including systolic and diastolic blood pressure, heart rate, seizure duration related to the procedure and recovery from sleep. Statistical analysis was performed using Student t test and Friedman test.
Results: There were 50 men and 34 women among included patients. The mean and standard deviation (SD) of age of patients in Nesdonal group in female and male were 40.5 ± 13.4 years and 30.2 ± 13.5 years, respectively. Data for propofol group was 36.5 ± 20.9 years and 25.7 ± 7.7 years for female and male patients, respectively. Nesdonal offered a superior hemodynamic stability during the procedure, and seizure duration has decreased with Nesdonal compared with propofol. However, patients who underwent propofol for their anesthesia recover faster from sleep, while systolic and diastolic blood pressure of this group were higher than Nesdonal group (P < 0.0001).
Conclusion: Considering better hemodynamic stability, it seems that Nesdonal is better than propofol for induction in ECT.

A Predictive Model for Assessment of Successful Outcome in Posterior Spinal Fusion Surgery

Mahsa Babaee, Paria Soleimani, Alireza Zali, Nima Mohseni Kabir, Mahmoud Chizari

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 143-151

Background: Low back pain is a common problem in many people. Neurosurgeons recommend Posterior Spinal Fusion Surgery (PSF) as one of the therapeutic strategies to the patients with low back pain. Due to the high risk of this type of surgery and the critical importance of making the right decision, accurate prediction of the surgical outcome is one of the main concerns for the neurosurgeons.

Methods: In this study, 12 types of Multi-Layer perceptron networks (MLP) and 66 Radial Basis Function (RBF) networks as the types of artificial neural network methods and a Logistic Regression model created and compared to predict the satisfaction with PSF surgery as one of the most well-known spinal surgeries.

Results: The most important clinical and radiologic features as twenty-seven factors for 480 patients (150 males, 330 females; mean age 52.32 ± 8.39 years) were considered as the model inputs that included: age, sex, type of disorder, duration of symptoms, job, walking distance without pain, walking distance without sensory disorders, visual analog scale scores, Japanese Orthopaedic Association score, diabetes, smoking, knee pain, pelvic pain, osteoporosis, spinal deformity and etc. The indexes such as receiver operating characteristic–area under curve (ROC-AUC), positive predictive value, negative predictive value and accuracy calculated to determine the best model. Postsurgical satisfaction was 77.5% at 6 months follow-up. The patients divided into the training, testing, and validation data sets.

Conclusion: The findings showed that the MLP model performed better in comparison with RBF and LR models for prediction of PSF surgery.

 

Forecasting Schizophrenia Incidence Frequencies Using Time Series Approach

Mohammad Ebrahim Ghaffari, Ali Ghaleiha, Zahra Taslimi, Fatemeh Sarvi, Payam Amini, Majid Sadeghifar, Saeid Yazdi-Ravandi

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 152-156

Introduction: Understanding the prevalence of schizophrenia has important implications for both health service planning and risk factor epidemiology. The aims of this study are to systematically identify and collate studies describing the prevalence of schizophrenia, to summarize the findings of these studies, and to explore selected factors that may influence prevalence estimates.

Methods: This historical cohort study was done on schizophrenia patients in Farshchian psychiatric hospital from April 2008 to April 2016. To analyze the data, the Holt-Winters Exponential Smoothing (HWES) method was applied. All the analyses were done by R.3.2.3. Software using the packages “forecast” and “tseries”. The statistical significant level was assumed as 0.05.

Results: Our investigation show that a constant frequency of Schizophrenia incidence happens every month from August 2008 to February 2015 while a considerable increase occurs in March 2015. The high frequency of Schizophrenia incidence remains constant to the end of 2015 and a decrease is shown in 2016. Also, data demonstrate the development of Schizophrenia in the next 24 months with 95% confidence interval.

Conclusion: Our study showed that a significant increase happens in the frequency of Schizophrenia from 2016. Although the development is not constant and the same for all months, the amount of increase is considerably high comparing to before 2016.

 

Coincidence of Anterior Communicating Artery Aneurysm in a Patient With Carotid Body Tumor: A Case Report

Afsoun Seddighi, Sima Behrouzian, Amir Nikouei, Amir Saied Seddighi

International Clinical Neuroscience Journal, Vol. 4 No. 4 (2017), 8 October 2017 , Page 157-159

Background: Intracranial aneurysms (IAs) are focal pathologic dilation of cerebral vasculature, which mostly affect the anterior circulation of brain. Carotid body tumors (CBTs) are the most common head and neck parasympathetic paragangliomas. These slow growing neoplasms may cause hypertension along with catecholamine release symptoms, mostly in patients in their fourth decade. This is the second reported case of simultaneous presentation of CBT and IA in a male patient.
Case Presentation: A 54-year-old male with positive history of hypertension presented with isolated acute weakness of right upper extremity. Bilateral Doppler ultrasound of carotid arteries showed a mass at left carotid bifurcation, which was confirmed by vessels computed tomography (CT) – angiography. CT scan also demonstrated anterior communicating artery (A-Com) aneurysm. Digital subtraction angiography (DSA) confirmed a right sided A-com artery aneurysm. Aneurismal repair was performed prior to CBT removal.
Conclusion: Although multifactorial etiologies, such as hypertension, atherosclerosis and congenital predisposition with vascular abnormalities exists; this case raises the possibility of etiologic relationship between hypertension and hypertensive crises due to catecholamine release and aneurismal development and rupture. Avoidance of possible life threatening complications of aneurismal rupture necessitates preoperative evaluation for CBT in patients with established diagnosis of IA.