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Classification of Human Emotions from Electroencephalogram (EEG) Signal Using Deep Neural Network
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 9, 2017 Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network Abeer Al-Nafjan Areej Al-Wabil College of Computer and Information Sciences Center for Complex Engineering Systems Imam Muhammad bin Saud University King Abdulaziz City for Science and Technology Riyadh, Saudi Arabia Riyadh, Saudi Arabia Manar Hosny Yousef Al-Ohali College of Computer and Information Sciences College of Computer and Information Sciences King Saud University King Saud University Riyadh, Saudi Arabia Riyadh, Saudi Arabia Abstract—Estimation of human emotions from [1]. Recognizing a user‘s affective state can be used to Electroencephalogram (EEG) signals plays a vital role in optimize training and enhancement of the BCI operations [2]. developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG is often used in BCI research experimentation because EEG-based emotion recognition. This was motivated by the the process is non-invasive to the research subject and minimal recent advances in accuracy and efficiency from applying deep risk is involved. The devices‘ usability, reliability, cost- learning techniques in pattern recognition and classification effectiveness, and the relative convenience of conducting applications. We adapted DNN to identify human emotions of a studies and recruiting participants due to their portability have given EEG signal (DEAP dataset) from power spectral density been cited as factors influencing the increased adoption of this (PSD) and frontal asymmetry features. The proposed approach is method in applied research contexts [3], [4]. These advantages compared to state-of-the-art emotion detection systems on the are often accompanied by challenges such as low spatial same dataset. -
Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents
J Happiness Stud DOI 10.1007/s10902-009-9150-9 RESEARCH PAPER Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents Peter Sheridan Dodds Æ Christopher M. Danforth Ó The Author(s) 2009. This article is published with open access at Springerlink.com Abstract The importance of quantifying the nature and intensity of emotional states at the level of populations is evident: we would like to know how, when, and why individuals feel as they do if we wish, for example, to better construct public policy, build more successful organizations, and, from a scientific perspective, more fully understand economic and social phenomena. Here, by incorporating direct human assessment of words, we quantify hap- piness levels on a continuous scale for a diverse set of large-scale texts: song titles and lyrics, weblogs, and State of the Union addresses. Our method is transparent, improvable, capable of rapidly processing Web-scale texts, and moves beyond approaches based on coarse categorization. Among a number of observations, we find that the happiness of song lyrics trends downward from the 1960s to the mid 1990s while remaining stable within genres, and that the happiness of blogs has steadily increased from 2005 to 2009, exhibiting a striking rise and fall with blogger age and distance from the Earth’s equator. Keywords Happiness Á Hedonometer Á Measurement Á Emotion Á Written expression Á Remote sensing Á Blogs Á Song lyrics Á State of the Union addresses 1 Introduction The desire for well-being and the avoidance of suffering arguably underlies all behavior (Argyle 2001; Layard 2005; Gilbert 2006; Snyder and Lopez 2009). -
Applying a Discrete Emotion Perspective
AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIVE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER Bachelor of Science in Psychology Ashland University May 2015 Submitted in partial fulfillment of requirements for the degree MASTER OF ARTS IN PSYCHOLOGY At the CLEVELAND STATE UNIVERSITY May 2019 We hereby approve this thesis For SARA E. LAUTZENHISER Candidate for the Master of Arts in Experimental Research Psychology For the Department of Psychology And CLEVELAND STATE UNIVERSITY’S College of Graduate Studies by __________________________ Eric Allard, Ph.D. __________________________ Department & Date __________________________ Andrew Slifkin, Ph. D. (Methodologist) __________________________ Department & Date __________________________ Conor McLennan, Ph.D. __________________________ Department & Date __________________________ Robert Hurley, Ph. D. __________________________ Department & Date Student’s Date of Defense May 10, 2019 AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER ABSTRACT While research in the psychology of human aging suggests that older adults are quite adept at managing negative affect, emotion regulation efficacy may depend on the discrete emotion elicited. For instance, prior research suggests older adults are more effective at dealing with emotional states that are more age-relevant/useful and lower in intensity (i.e., sadness) relative to less relevant/useful or more intense (i.e., anger). The goal of the present study was to probe this discrete emotions perspective further by addressing the relevance/intensity distinction within a broader set of negative affective states (i.e., fear and disgust, along with anger and sadness). Results revealed that participants reported relatively high levels of the intended emotion for each video, while also demonstrating significant affective recovery after the attentional refocusing task. -
DISGUST: Features and SAWCHUK and Clinical Implications
Journal of Social and Clinical Psychology, Vol. 24, No. 7, 2005, pp. 932-962 OLATUNJIDISGUST: Features AND SAWCHUK and Clinical Implications DISGUST: CHARACTERISTIC FEATURES, SOCIAL MANIFESTATIONS, AND CLINICAL IMPLICATIONS BUNMI O. OLATUNJI University of Massachusetts CRAIG N. SAWCHUK University of Washington School of Medicine Emotions have been a long–standing cornerstone of research in social and clinical psychology. Although the systematic examination of emotional processes has yielded a rather comprehensive theoretical and scientific literature, dramatically less empirical attention has been devoted to disgust. In the present article, the na- ture, experience, and other associated features of disgust are outlined. We also re- view the domains of disgust and highlight how these domains have expanded over time. The function of disgust in various social constructions, such as cigarette smoking, vegetarianism, and homophobia, is highlighted. Disgust is also becoming increasingly recognized as an influential emotion in the onset, maintenance, and treatment of various phobic states, Obsessive–Compulsive Disorder, and eating disorders. In comparison to the other emotions, disgust offers great promise for fu- ture social and clinical research efforts, and prospective studies designed to improve our understanding of disgust are outlined. The nature, structure, and function of emotions have a rich tradition in the social and clinical psychology literature (Cacioppo & Gardner, 1999). Although emotion theorists have contested over the number of discrete emotional states and their operational definitions (Plutchik, 2001), most agree that emotions are highly influential in organizing thought processes and behavioral tendencies (Izard, 1993; John- Preparation of this manuscript was supported in part by NIMH NRSA grant 1F31MH067519–1A1 awarded to Bunmi O. -
About Emotions There Are 8 Primary Emotions. You Are Born with These
About Emotions There are 8 primary emotions. You are born with these emotions wired into your brain. That wiring causes your body to react in certain ways and for you to have certain urges when the emotion arises. Here is a list of primary emotions: Eight Primary Emotions Anger: fury, outrage, wrath, irritability, hostility, resentment and violence. Sadness: grief, sorrow, gloom, melancholy, despair, loneliness, and depression. Fear: anxiety, apprehension, nervousness, dread, fright, and panic. Joy: enjoyment, happiness, relief, bliss, delight, pride, thrill, and ecstasy. Interest: acceptance, friendliness, trust, kindness, affection, love, and devotion. Surprise: shock, astonishment, amazement, astound, and wonder. Disgust: contempt, disdain, scorn, aversion, distaste, and revulsion. Shame: guilt, embarrassment, chagrin, remorse, regret, and contrition. All other emotions are made up by combining these basic 8 emotions. Sometimes we have secondary emotions, an emotional reaction to an emotion. We learn these. Some examples of these are: o Feeling shame when you get angry. o Feeling angry when you have a shame response (e.g., hurt feelings). o Feeling fear when you get angry (maybe you’ve been punished for anger). There are many more. These are NOT wired into our bodies and brains, but are learned from our families, our culture, and others. When you have a secondary emotion, the key is to figure out what the primary emotion, the feeling at the root of your reaction is, so that you can take an action that is most helpful. . -
Preverbal Infants Match Negative Emotions to Events
Developmental Psychology © 2019 American Psychological Association 2019, Vol. 55, No. 6, 1138–1149 0012-1649/19/$12.00 http://dx.doi.org/10.1037/dev0000711 How Do You Feel? Preverbal Infants Match Negative Emotions to Events Ashley L. Ruba, Andrew N. Meltzoff, and Betty M. Repacholi University of Washington There is extensive disagreement as to whether preverbal infants have conceptual categories for different emotions (e.g., anger vs. disgust). In addition, few studies have examined whether infants have conceptual categories of emotions within the same dimension of valence and arousal (e.g., high arousal, negative emotions). The current experiments explore one aspect of infants’ ability to form conceptual categories of emotions: event-emotion matching. Three experiments investigated whether infants match different negative emotions to specific events. In Experiment 1, 14- and 18-month-olds were randomly assigned to 1 of 3 negative emotion conditions (Anger, Fear, or Disgust). Infants were familiarized with an Emoter interacting with objects in an anger-eliciting event (Unmet Goal) and a disgust-eliciting event (New Food). After each event, the Emoter expressed an emotion that was either congruent or incongruent with the event. Infants matched unmet goals to the expression of anger. However, neither age matched the expression of disgust to an event involving exposure to new food. To probe whether this was a design artifact, a revised New Food event and a fear-congruent event (Strange Toy) were created for Experiment 2. Infants matched the expression of disgust to the new food event, but they did not match fear to an event involving an unfamiliar object. -
Disgust: Evolved Function and Structure
Psychological Review © 2012 American Psychological Association 2013, Vol. 120, No. 1, 65–84 0033-295X/13/$12.00 DOI: 10.1037/a0030778 Disgust: Evolved Function and Structure Joshua M. Tybur Debra Lieberman VU University Amsterdam University of Miami Robert Kurzban Peter DeScioli University of Pennsylvania Brandeis University Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and that of information processing. Although there is widespread agreement that disgust evolved to motivate the avoidance of contact with disease-causing organisms, there is no consensus about the functions disgust serves when evoked by acts unrelated to pathogen avoidance. Here we suggest that in addition to motivating pathogen avoidance, disgust evolved to regulate decisions in the domains of mate choice and morality. For each proposed evolved function, we posit distinct information processing systems that integrate function-relevant information and account for the trade-offs required of each disgust system. By refocusing the discussion of disgust on computational mechanisms, we recast prior theorizing on disgust into a framework that can generate new lines of empirical and theoretical inquiry. Keywords: disgust, adaptation, evolutionary psychology, emotion, cognition Research concerning disgust has expanded in recent years (Ola- selection pressure driving the evolution of the disgust system, but tunji & Sawchuk, 2005; Rozin, Haidt, & McCauley, 2009), and there has been less precision in identifying the selection pressures contemporary disgust researchers generally agree that an evolu- driving the evolution of disgust systems unrelated to pathogen tionary perspective is necessary for a comprehensive understand- avoidance (e.g., behavior in the sexual and moral domains). -
Bodily Maps of Emotions
Bodily maps of emotions Lauri Nummenmaaa,b,c,1, Enrico Glereana, Riitta Harib,1, and Jari K. Hietanend aDepartment of Biomedical Engineering and Computational Science and bBrain Research Unit, O. V. Lounasmaa Laboratory, School of Science, Aalto University, FI-00076, Espoo, Finland; cTurku PET Centre, University of Turku, FI-20521, Turku, Finland; and dHuman Information Processing Laboratory, School of Social Sciences and Humanities, University of Tampere, FI-33014, Tampere, Finland Contributed by Riitta Hari, November 27, 2013 (sent for review June 11, 2013) Emotions are often felt in the body, and somatosensory feedback independence of bodily topographies across emotions. We pro- has been proposed to trigger conscious emotional experiences. pose that consciously felt emotions are associated with culturally Here we reveal maps of bodily sensations associated with different universal, topographically distinct bodily sensations that may emotions using a unique topographical self-report method. In five support the categorical experience of different emotions. n = experiments, participants ( 701) were shown two silhouettes of Results bodies alongside emotional words, stories, movies, or facial expres- sions. They were asked to color the bodily regions whose activity We ran five experiments, with 36–302 participants in each. In they felt increasing or decreasing while viewing each stimulus. experiment 1, participants reported bodily sensations associated “ ” “ ” Different emotions were consistently associated with statistically with six basic and seven nonbasic ( complex ) emotions, as separable bodily sensation maps across experiments. These maps well as a neutral state, all described by the corresponding emo- were concordant across West European and East Asian samples. tion words. Fig. 2 shows the bodily sensation maps associated Statistical classifiers distinguished emotion-specific activation maps with each emotion. -
Fear, Anger, and Risk
Journal of Personality and Social Psychology Copyright 2001 by the American Psychological Association, Inc. 2001. Vol. 81. No. 1, 146-159 O022-3514/01/$5.O0 DOI. 10.1037//O022-3514.81.1.146 Fear, Anger, and Risk Jennifer S. Lemer Dacher Keltner Carnegie Mellon University University of California, Berkeley Drawing on an appraisal-tendency framework (J. S. Lerner & D. Keltner, 2000), the authors predicted and found that fear and anger have opposite effects on risk perception. Whereas fearful people expressed pessimistic risk estimates and risk-averse choices, angry people expressed optimistic risk estimates and risk-seeking choices. These opposing patterns emerged for naturally occurring and experimentally induced fear and anger. Moreover, estimates of angry people more closely resembled those of happy people than those of fearful people. Consistent with predictions, appraisal tendencies accounted for these effects: Appraisals of certainty and control moderated and (in the case of control) mediated the emotion effects. As a complement to studies that link affective valence to judgment outcomes, the present studies highlight multiple benefits of studying specific emotions. Judgment and decision research has begun to incorporate affect In the present studies we follow the valence tradition by exam- into what was once an almost exclusively cognitive field (for ining the striking influence that feelings can have on normatively discussion, see Lerner & Keltner, 2000; Loewenstein & Lerner, in unrelated judgments and choices. We diverge in an important way, press; Loewenstein, Weber, Hsee, & Welch, 2001; Lopes, 1987; however, by focusing on the influences of specific emotions rather Mellers, Schwartz, Ho, & Ritov, 1997). To date, most judgment than on global negative and positive affect (see also Bodenhausen, and decision researchers have taken a valence-based approach to Sheppard, & Kramer, 1994; DeSteno et al, 2000; Keltner, Ells- affect, contrasting the influences of positive-affect traits and states worth, & Edwards, 1993; Lerner & Keltner, 2000). -
What Disgust Does and Does Not Do for Moral Cognition Jared Piazzaa
What Disgust Does and Does Not Do for Moral Cognition Jared Piazzaa, Justin F. Landyb, Alek Chakroffc Liane Youngd, Emily Wassermand a Lancaster University, Department of Psychology b University of Chicago Booth School of Business cCharlie Finance Co., San Francisco, CA dBoston College, Psychology Department 2 1. Introduction Disgust is typically characterized as a negative emotion associated with the rejection of distasteful or contaminating objects (Rozin and Fallon 1987). The physiological aspects of disgust involve nausea and loss of appetite, and the bodily expression of disgust includes behaviors (e.g., gagging, vomiting) designed to orally block or expel noxious substances (Ekman and Friesen 1971; Royzman, Leeman and Sabini 2008; Rozin, Haidt and McCauley 2008; Yoder, Widen and Russell 2016). The canonical elicitors of disgust are well documented: many people report feeling nauseous or sick at the sight or smell of oral contaminants (e.g., rotten food, bodily waste) and/or disease vectors (e.g., blood, skin maladies, sexual fluids, certain animals; Curtis, Aunger and Rabie, 2004; Haidt, McCauley and Rozin, 1994; Olatunji et al. 2007). It is uncontroversial that disgust can also be evoked in the context of a moral offense. What remains controversial is disgust’s role or relevance within a moral context. When Armin Meiwes, the Rotenburg Cannibal, was discovered to have eaten the severed penis of his voluntary victim, before killing him and consuming his flesh over the next ten months, the story of this crime undoubtedly aroused disgust (and horror) in many of us. The relevant question is not whether we felt disgust about this crime—for most of us, human penis is not on the menu, and the thought of Meiwes’ preferred cuisine is deeply distasteful. -
From Desire Coherence and Belief Coherence to Emotions: a Constraint Satisfaction Model
From desire coherence and belief coherence to emotions: A constraint satisfaction model Josef Nerb University of Freiburg Department of Psychology 79085 Freiburg, Germany http://www.psychologie.uni-freiburg.de/signatures/nerb/ [email protected] Abstract The model is able to account for the elicitation of discrete emotions using these five criteria. In the DEBECO archi- Appraisal theory explains the elicitation of emotional reactions as a consequence of subjective evaluations tecture, the five criteria evolve out of three basic principles: based on personal needs, goals, desires, abilities, and belief coherence, desire coherence and belief-desire coher- beliefs. According to the appraisal approach, each emo- ence. Based on these principles, which are all well sup- tion is caused by a characteristic pattern of appraisals, ported by empirical evidence from psychological research, and different emotions are associated with different ap- DEBECO also allows the representation of two elementary praisals. This paper presents the DEBECO architec- types of goals: approach goals and avoidance goals. The ture, a computational framework for modeling the ap- DEBECO architecture is implemented as a parallel con- praisal process. DEBECO is based upon three core straint satisfaction network and is an extension of Thagard’s coherence principles: belief coherence, desire coher- HOTCO model (Thagard, 2000, 2003; Thagard & Nerb, ence and belief-desire coherence. These three coher- 2002). ence mechanisms allow two elementary types of goals to be represented: approach and avoidance goals. By Within DEBECO, emotions are seen as valenced reac- way of concrete simulation examples, it is shown how tions to events, persons or objects, with their particular na- discrete emotions such as anger, pride, sadness, shame, ture being determined by the way in which the eliciting situ- surprise, relief and disappointment emerge out of these ation is construed (cf. -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection.