@article{Charara2017,
title = {The burden of mental disorders in the eastern mediterranean region, 1990-2013},
author = {R Charara and M Forouzanfar and M Naghavi and M Moradi-Lakeh and A Afshin and T Vos and F Daoud and H Wang and C E Bcheraoui and I Khalil and R R Hamadeh and A Khosravi and V Rahimi-Movaghar and Y Khader and N Al-Hamad and C M Obermeyer and A Rafay and R Asghar and S M Rana and A Shaheen and N M E Abu-Rmeileh and A Husseini and L J Abu-Raddad and T Khoja and Z A A Rayess and F S AlBuhairan and M Hsairi and M A Alomari and R Ali and G Roshandel and A S Terkawi and S Hamidi and A H Refaat and R Westerman and A A Kiadaliri and A S Akanda and S D Ali and U Bacha and A Badawi and S Bazargan-Hejazi and I A D Faghmous and S -M Fereshtehnejad and F Fischer and J B Jonas and B K Defo and A Mehari and S B Omer and F Pourmalek and O A Uthman and A A Mokdad and F T Maalouf and F Abd-Allah and N Akseer and D Arya and R Borschmann and A Brazinova and T S Brugha and F Catala-Lopez and L Degenhardt and A Ferrari and J M Haro and M Horino and J C Hornberger and H Huang and C Kieling and D Kim and Y Kim and A K Knudsen and P B Mitchell and G Patton and R Sagar and M Satpathy and K Savuon and S Seedat and I Shiue and J C Skogen and D J Stein and K M Tabb and H A Whiteford and P Yip and N Yonemoto and C J L Murray and A H Mokdad},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009892168&doi=10.1371%2fjournal.pone.0169575&partnerID=40&md5=471830ec1239e37c6fc4681bed5698f6},
doi = {10.1371/journal.pone.0169575},
issn = {19326203},
year = {2017},
date = {2017-01-01},
journal = {PLoS ONE},
volume = {12},
number = {1},
publisher = {Public Library of Science},
abstract = {The Eastern Mediterranean Region (EMR) is witnessing an increase in chronic disorders, including mental illness. With ongoing unrest, this is expected to rise. This is the first study to quantify the burden of mental disorders in the EMR. We used data from the Global Burden of Disease study (GBD) 2013. DALYs (disability-adjusted life years) allow assessment of both premature mortality (years of life lost-YLLs) and nonfatal outcomes (years lived with disability-YLDs). DALYs are computed by adding YLLs and YLDs for each age-sex-country group. In 2013, mental disorders contributed to 5.6% of the total disease burden in the EMR (1894 DALYS/100,000 population): 2519 DALYS/100,000 (2590/100,000 males, 2426/100,000 females) in high-income countries, 1884 DALYS/100,000 (1618/100,000 males, 2157/100,000 females) in middle-income countries, 1607 DALYS/100,000 (1500/100,000 males, 1717/100,000 females) in low-income countries. Females had a greater proportion of burden due to mental disorders than did males of equivalent ages, except for those under 15 years of age. The highest proportion of DALYs occurred in the 25-49 age group, with a peak in the 35-39 years age group (5344 DALYs/100,000). The burden of mental disorders Burden of Mental Disorders in EMR PLOS ONE in EMR increased from 1726 DALYs/100,000 in 1990 to 1912 DALYs/100,000 in 2013 (10.8% increase). Within the mental disorders group in EMR, depressive disorders accounted for most DALYs, followed by anxiety disorders. Among EMR countries, Palestine had the largest burden of mental disorders. Nearly all EMR countries had a higher mental disorder burden compared to the global level. Our findings call for EMR ministries of health to increase provision of mental health services and to address the stigma of mental illness. Moreover, our results showing the accelerating burden of mental health are alarming as the region is seeing an increased level of instability. Indeed, mental health problems, if not properly addressed, will lead to an increased burden of diseases in the region. © 2017 Charara et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.},
note = {cited By 30},
keywords = {80 and Over, Adolescent, Adult, Age, Age Factors, Aged, Anxiety Disorder, Article, Attention Deficit Disorder, Autism, Bipolar Disorder, Children, Conduct Disorder, Depression, Elderly People, Female, Global Health, Groups by Age, Health Status, Highest Income Group, Human, Infant, Intellectual Impairment, Kuwait, Life Expectancy, Major Clinical Study, Male, Mediterranean Region, Mental Disease, Mental Disorders, Mental Health, Mental Health Service, Middle Aged, Middle Income Group, Mortality, Newborn, Palestine, Premature Mortality, Preschool, Preschool Child, Prevalence, Qatar, Quality Adjusted Life Year, Schizophrenia, Sex Difference, Sex Factors, Southern Europe, Time Factor, Time Factors, United Arab Emirates, Young Adult},
pubstate = {published},
tppubtype = {article}
}

@article{Cassidy2014112,
title = {Can adults with autism spectrum disorders infer what happened to someone from their emotional response?},
author = {S Cassidy and D Ropar and P Mitchell and P Chapman},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894307909&doi=10.1002%2faur.1351&partnerID=40&md5=8c6736bc006e9eebde29427879d023c3},
doi = {10.1002/aur.1351},
issn = {19393792},
year = {2014},
date = {2014-01-01},
journal = {Autism Research},
volume = {7},
number = {1},
pages = {112-123},
publisher = {John Wiley and Sons Inc.},
abstract = {Can adults with autism spectrum disorders (ASD) infer what happened to someone from their emotional response? Millikan has argued that in everyday life, others' emotions are most commonly used to work out the antecedents of behavior, an ability termed retrodictive mindreading. As those with ASD show difficulties interpreting others' emotions, we predicted that these individuals would have difficulty with retrodictive mindreading. Sixteen adults with high-functioning autism or Asperger's syndrome and 19 typically developing adults viewed 21 video clips of people reacting to one of three gifts (chocolate, monopoly money, or a homemade novelty) and then inferred what gift the recipient received and the emotion expressed by that person. Participants' eye movements were recorded while they viewed the videos. Results showed that participants with ASD were only less accurate when inferring who received a chocolate or homemade gift. This difficulty was not due to lack of understanding what emotions were appropriate in response to each gift, as both groups gave consistent gift and emotion inferences significantly above chance (genuine positive for chocolate and feigned positive for homemade). Those with ASD did not look significantly less to the eyes of faces in the videos, and looking to the eyes did not correlate with accuracy on the task. These results suggest that those with ASD are less accurate when retrodicting events involving recognition of genuine and feigned positive emotions, and challenge claims that lack of attention to the eyes causes emotion recognition difficulties in ASD. Autism Res 2014, 7: 112-123. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.},
note = {cited By 21},
keywords = {Accuracy, Adult, Aged, Article, Asperger Syndrome, Attention, Autism, Behaviour, Cacao, Child Development Disorders, Clinical Article, Concept Formation, Controlled Study, Deception, Discrimination (Psychology), Emotion, Eye Movement, Eye Tracking, Face Processing, Facial Expression, Female, Human, Interpersonal Relations, Male, Middle Aged, Money, Pervasive, Priority Journal, Recipient, Recognition, Reference Values, Retrodictive Mindreading, Spontaneous Emotion Recognition, Theory of Mind, Video Recording, Young Adult},
pubstate = {published},
tppubtype = {article}
}

@article{Selvaraj2013,
title = {Classification of emotional states from electrocardiogram signals: A non-linear approach based on hurst},
author = {J Selvaraj and M Murugappan and K Wan and S Yaacob},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879017985&doi=10.1186%2f1475-925X-12-44&partnerID=40&md5=18c5309ac9f3017f455480f1ff732a30},
doi = {10.1186/1475-925X-12-44},
issn = {1475925X},
year = {2013},
date = {2013-01-01},
journal = {BioMedical Engineering Online},
volume = {12},
number = {1},
publisher = {BioMed Central Ltd.},
abstract = {Background: Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person. However, the performance of various methods developed so far lacks accuracy, and more robust methods need to be developed to identify the emotional pattern associated with ECG signals.Methods: Emotional ECG data was obtained from sixty participants by inducing the six basic emotional states (happiness, sadness, fear, disgust, surprise and neutral) using audio-visual stimuli. The non-linear feature 'Hurst' was computed using Rescaled Range Statistics (RRS) and Finite Variance Scaling (FVS) methods. New Hurst features were proposed by combining the existing RRS and FVS methods with Higher Order Statistics (HOS). The features were then classified using four classifiers - Bayesian Classifier, Regression Tree, K- nearest neighbor and Fuzzy K-nearest neighbor. Seventy percent of the features were used for training and thirty percent for testing the algorithm.Results: Analysis of Variance (ANOVA) conveyed that Hurst and the proposed features were statistically significant (p < 0.001). Hurst computed using RRS and FVS methods showed similar classification accuracy. The features obtained by combining FVS and HOS performed better with a maximum accuracy of 92.87% and 76.45% for classifying the six emotional states using random and subject independent validation respectively.Conclusions: The results indicate that the combination of non-linear analysis and HOS tend to capture the finer emotional changes that can be seen in healthy ECG data. This work can be further fine tuned to develop a real time system. © 2013 Selvaraj et al.; licensee BioMed Central Ltd.},
note = {cited By 42},
keywords = {Adolescent, Adult, Aged, Article, Audio-Visual Stimulus, Autonomous Nervous Systems, Children, Classification Accuracy, Computer Based Training, Computer-Assisted, Electrocardiogram Signal, Electrocardiography, Emotion, Female, Fuzzy K-nearest Neighbor, Higher-Order Statistic (HOS), Human, Intellectual Disability, Interactive Computer Systems, Methodology, Middle Aged, Nonlinear Dynamics, Nonlinear System, Procedures, Real Time Systems, Signal Processing, Statistics, Young Adult},
pubstate = {published},
tppubtype = {article}
}