Program 15 Day of Clinical Research
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10 Inducing and Measuring Emotion and Affect
1 CN 10 CT Inducing and Measuring Emotion and Affect: Tips, Tricks, and Secrets CA Karen S. Quigley, Kristen A. Lindquist and Lisa Feldman Barrett Every person (barring those with a brain disorder) knows what it feels like to be moved by something – to feel energized or defeated, anxious or tranquil. Even without labeling these feelings, or being aware of them in an explicit way, such feelings exist as states of mind or can be observed in certain actions. In the Western views of the human mind that ground scientific psychology, such states are referred to as “emotional” or “affective” (as distinguished from “cognitive” or “perceptual”).1 These two words – “emotion” and “affect” – have caused great confusion in the scientific literature because they are used by some authors to denote two different classes of phenomena, whereas others use these words interchangeably. In English, the word “affect” literally means “to produce a change,” whereas the word “emotion” derives from the French word “to stir up” and the Latin word “to move.” In psychological discourse, “affect” has sometimes been used to refer to free-floating feelings whereas “emotion” has referred to feelings in response to a specific triggering event (e.g., James, 1890). The word “affect” also has been used to refer to feelings that accompany emotions such as anger, sadness, fear, happiness, and so on, which are defined as physical states (e.g., Panksepp, 1998). “Affect” has been used as a general term to mean anything emotional (e.g., Davidson, Scherer, & Goldsmith, 2003), allowing researchers to XML Typescript © Cambridge University Press – Generated by Aptara. -
Analysis of Machine Learning Algorithms for the Recognition of Basic Emotions: Data Mining of Psychophysiological Sensor Information
Ulm University Medical Center Department of Psychosomatic Medicine and Psychotherapy Director: Prof. Dr. Harald Gündel Section Medical Psychology Analysis of Machine Learning Algorithms for the Recognition of Basic Emotions: Data Mining of Psychophysiological Sensor Information Dissertation submitted to obtain the doctoral degree of Human Biology of the Medical Faculty of Ulm University By Lin Zhang born in Tianjin, P.R. China 2019 Acting Dean: Prof. Dr. Thomas Wirth 1st reviewer: Prof. Dr. Harald C. Traue 2nd reviewer: PD Dr. Friedhelm Schwenker Day of Graduation: May 17, 2019 For all my friends and my family CONTENT ABBREVIATIONS VI LIST OF TABLES VIII LIST OF FIGURES IX CHAPTER 1 INTRODUCTION 1 1.1 Emotion 1 1.1.1. Major types of emotion elicitations in experimental designs 3 1.1.2. Emotion-specific physiological responses 5 1.2 Affective Computing 8 1.3 Machine Learning and pattern recognition 8 1.3.1 Classification methods 10 1.3.2 The performance of a classifier 15 1.3.3 Feature selection methods 18 1.4 The state of research on emotion classification based on psychophysiological signals 19 1.5 Aims of this dissertation 21 CHAPTER 2 MATERIAL AND METHODS 22 2.1 Participants 22 2.2 Measured psychophysiological parameters 23 2.2.1 The Electrodermal activity 24 2.2.2 Electrocardiogram 25 2.2.3 Electromyography 26 2.3 The experimental procedure 28 2.3.1 Film clips for emotion elicitation 28 2.3.2 Setup and the preparation for the experiment 29 2.3.3 The procedure of emotion experiment 31 2.4 The analysis of subjective ratings 31 2.5 The -
Facial Expressions in EEG/EMG Recordings
University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Department of Human Media Interaction Master of Science Thesis Facial expressions in EEG/EMG recordings. by Lennart Boot Supervisor: Christian M¨uhl Enschede, 2008/2009 Abstract With focus on natural intuitive interaction of humans with their media, new ways of interacting are being studied. Brain computer interface (BCI), originally focussed on people with disabilities, is a relative new field for providing natural interactivity between a user and a computer. Using scalp EEG caps, healthy consumers can potentially use BCI applications for daily entertaining purposes, for example gaming. Using facial expressions on the other hand is one of the most natural ways of non verbal communication. At the moment, there are several different techniques for a computer to read facial expressions. EEG recording is one of them that is hardly or not at all studied at the present, but would make an interesting addition for commercial BCI devices. Because actual consumers are believed to be only interested in how well a device works, rather than how it works, it was decided to also look at EMG signals visible in recordings done with an EEG recording device. Thus the topic of this research is facial expressions in recordings from a scalp EEG device, rather than facial expressions in BCI. It was expected that EMG signals, visible in recorded EEG data, are bigger than the EEG signals them self. The goals of this study were to gather EEG and EMG data, recorded with an EEG device, of voluntary facial expressions, and to analyze it. -
Usage of Social Neuroscience in E-Commerce Research - Current Research and Future Opportunities
Journal of Theoretical and Applied Electronic Commerce Research This paper is available online at ISSN 0718–1876 Electronic Version www.jtaer.com VOL 13 / ISSUE 1 / JANUARY 2018 / I-IX DOI: 10.4067/S0718-18762018000100101 © 2018 Universidad de Talca - Chile Editorial: Usage of Social Neuroscience in E-Commerce Research - Current Research and Future Opportunities Mirjana Pejić Bach University of Zagreb, Faculty of Economics & Business, Department of Informatics, Zagreb, Croatia, Co-Editor [email protected] January 2018 Introduction Electronic commerce (e-commerce) has become one of the main drivers of the digital transformation of both national and global economies. E-commerce was defined as a process including both the sell-buy relationships and transactions among companies and individuals, and “the corporate processes that support the commerce within individual firms” [17]. E-commerce, also known as e-business, has become a widespread term in the late 90’s, while it has been present for much longer period of time, from 80’s [16]. Two main types of e-commerce are defined, based on the types of clients: business-to-business (B2B) and business-to-customers (B2C). However, the emergence of social media and peer-to-peer networks enticed the additional type of e-commerce: customers-to-customers (C2C), in which transactions are exchanged not only for money, but also in exchange for personal services or other goods. In addition, due to the prevalent usage of smart-phones, e-commerce has become often referred to as m-commerce [2]. Research area of e-commerce is composed by many scientific disciplines, such as computer science, psychology, economics, and natural sciences, and applied areas, such as marketing, management, finance and engineering [5]. -
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PPSYP_C1.inddSYP_C1.indd 1 003/07/173/07/17 77:02:02 AAMM PSYCHOPHYSIOLOGY THE INTERNATIONAL JOURNAL OF THE SOCIETY FOR PSYCHOPHYSIOLOGICAL RESEARCH Editor Monica Fabiani University of Illinois at Urbana-Champaign Senior Associate Editor Diane Filion Andreas Keil University of Missouri-Kansas City, USA University of Florida, USA J. Richard Jennings Sarah Laszlo University of Pittsburgh, USA Lisa Gatzke-Kopp Pennsylvania State University, USA Binghamton University, SUNY, USA Associate Editors Stephan Moratti Greg Hajcak University of Madrid, Spain Mustafa al'Absi Florida State University, USA University of Minnesota Medical School, USA Anna Whittaker (Phillips) Bruce D. Bartholow Erin A. Hazlett University of Birmingham, United Kingdom University of Missouri, USA Icahn School of Medicine at Mount Sinai, USA Brigitte Rockstroh Brett Clementz James J. Peters Veterans Affairs Medical Center, USA University of Konstanz, Germany University of Georgia, USA Ursula Hess Edward Vogel Florin Dolcos Humboldt University, Germany University of Chicago, USA University of Illinois at János Horváth Urbana-Champaign, USA Kara Federmeier Hungarian Academy of Sciences, Budapest, Hungary University of Illinois at Frini Karayanidis Urbana-Champaign, USA University of Newcastle, Australia SOCIETY FOR PSYCHOPHYSIOLOGICAL RESEARCH An international society that fosters research relating psychology and physiology. Officers President: Cindy Yee-Bradbury Secretary: Bruce D. Bartholow Past-President: Ottmar Lipp Treasurer:GregHajcak President-Elect: Kara Federmeier Board of Directors Paul Corballis Sarah Laszlo Michelle Shiota Bruce Friedman Gregory A. Miller Sarah Sass Christine Larson Harald Schupp Standing Committee Chairs Archives Judy Ford Membership Mary Burleson Bylaws Ursula Hess Nomination Karen Quigley Student Interests Sarah Sass Outreach Ottmar Lipp & Cindy Yee-Bradbury Convention Sites Erin Hazlett & Harald Schupp Program Markus Ullsperger Distinguished Contributions Publication Gregory A.