Automated emotion recognition (AEE) is an important issue in various fields of activities which use human emotional reactions as a signal for marketing, technical equipment, or human–robot interaction. This paper analyzes scientific research and technical papers for sensor use analysis, among various methods implemented or researched. This paper covers a few classes of sensors, using contactless methods as well as contact and skin-penetrating electrodes for human emotion detection and the measurement of their intensity. The results of the analysis performed in this paper present applicable methods for each type of emotion and their intensity and propose their classification. The classification of emotion sensors is presented to reveal area of application and expected outcomes from each method, as well as their limitations. This paper should be relevant for researchers using human emotion evaluation and analysis, when there is a need to choose a proper method for their purposes or to find alternative decisions. Based on the analyzed human emotion recognition sensors and methods, we developed some practical applications for humanizing the Internet of Things (IoT) and affective computing systems.

Human Emotion Recognition: Review of Sensors and Methods.

Although generally philosophers have put a high valuation on reason, increasingly the role of emotions in motivating action is being recognized. The essays in this volume explore the emotions from a variety of perspectives, ranging from Aristotelian views of the passions to the new findings of cognitive science, and from such diverse starting points as medieval literature and psychological studies.

Philosophy of the Emotions

The purpose of this article is to describe an internet-based platform for improving symptoms and quality of life for people with psychological and behavioural health problems such as depression, an ...

Features and functionality of the Iterapi platform for internet-based psychological treatment

Coming Attractions: reading American movie trailers

NEIL R. CARLSON, WILLIAM BUSKIST, MICHAEL E. ENZLE, and C. DONALD HETH Psychology: The Science of Behaviour Toronto, ON: Pearson Education Canada Ltd., 2002, 701 pages (ISBN 0-13-0393606-6, $105.95, Hardcover) Reviewed by GEORGE ALDER With the publication of the second Canadian edition of Psychology: The Science of Behaviour, the already difficult decision facing introductory textbook selection committees in psychology departments across Canadian universities and colleges has become more complicated. This is the second edition of a Canadian adaptation of Neil Carlson and William Buskist's introductory text that, when it was last published in 1997, was in its fifth edition. Michael Enzle and C. Donald Heth of the University of Alberta have done an admirable job of "Canadianizing" the Carlson and Buskist text, providing a book in which Canadian sources and statistics are seamlessly integrated into the body of the text. Enzle and Heth have avoided many of the more common methods of "Canadianizing" texts (e.g., merely adding Canadian source materials to the end of already existing sections or by highlighting Canadian content by using specialized fonts), and in doing so have provided a text that deserves to be considered on its own merits, not merely on the basis of its Canadian content. Considering the depth and breadth of material covered, this text would be most appropriate for use in institutions where the instruction of introductory psychology extends across two semesters. The 635 pages of text (excluding prefaces, indexes, references, etc.) are divided into 18 chapters of just over 35 pages in average length. These numbers are comparable to those obtained in a recent analysis of full-- length introductory psychology textbooks that reported an average of 673.7 text pages divided into 17.62 chapters for an average of 38.61 pages per chapter (Griggs, Jackson, Christopher, & Marek, 1999). The breadth and depth of coverage in Carlson et al. is reflected not only by its length but also by the inclusion of separate chapters for the topics of sensation and perception which are in many texts combined into a single chapter, and with a separate chapter for language, which is often integrated into other more general topics (e.g., intelligence, development). One question that is often of paramount importance to committee members in selecting introductory texts is the text's level of difficulty. In their 1989 survey of psychology authors and editors, Griggs and Jackson found that introductory textbooks can be divided into three levels on the basis of their difficulty. A higher-level text is one that "...covers psychology in the greatest depth and breadth and is also closely tied to the experimental literature" (Griggs & Jackson, 1989, p. 62), whereas a middle-level text has the breadth of coverage but not the depth, and a lower-level text represents yet another level down in depth of coverage with substantial in-chapter pedagogy (Griggs & Jackson, 1989). In his analysis of the difficulty of 37 introductory texts, Griggs (1999) rated the fifth edition of the Carlson and Buskist (1997) text as a "Higher" level text. Given that the Canadian edition of this text continues to be tied closely to the research literature and has retained the same basic structure and pedagogy, one could reasonably argue that the Canadian adaptation of the text would also receive a "Higher" level rating. Another factor that is often of major concern to those selecting introductory textbooks is the nature of the pedagogical features incorporated into the text. The Canadian edition of the Carlson et al. text has a number of different pedagogical aids, some of which I found more effective than others. Each chapter begins with a "Chapter Outline" that provides a survey of what the chapter discusses. I assume that many students will forego reading these since they do not really cover any additional material. However, I found the "Opening Vignettes" presented immediately after the chapter outlines to be considerably more compelling. …

Psychology: The Science of Behaviour

The omnichannel business has deeply affected retail practices and promotional strategies. This paper presents an empirical evaluation of omnichannel advertisement channels using neurometric respons...

Use of neurometrics to choose optimal advertisement method for omnichannel business

This paper intends to decode depressive disorder using computer vision. Facial expressions rendered by a depressive and non-depressive person were studied against a given stimulus. A survey was conducted using Attention Deficit Hyperactivity Disorder (ADHD) questionnaire on a group of four hundred one volunteers between age group of nineteen to twenty-three years. A total of 254 male and 147 female volunteers participated in survey. Three hundred and eighty-seven responses were actually received and seventy-two respondents were identified as potential patients of depressive disorder. Amongst these anticipated depressive patients, thirty-eight were called for a personal assessment/ interview by practicing psychologists as per DSM-V standards. Data collected from these respondents were used to train a Convolutional Neural Network model, so as to classify a person as depressed or not depressed. The proposed system attained a precision of 74 in the identification of depressive patients. This study concludes to the fact that facial expressions rendered by a patient suffering from the depressive disorder are different from that of non-depressive person against any given psychological stimulus. Further, it was also concluded that facial expressions rendered by a respondent against any annotated quality stimulus like ADFES dataset could provide results comparable to that of ADHD questionnaire. The outcome of this research intends to facilitate doctors to identify potential depressive patients and make an early diagnosis.

Decoding depressive disorder using computer vision

JavaScript Object Notation (JSON) is a syntax for exchanging and storing data, the text data is converted in Object form and processed. The consistency and data integrity are the big challenges of payload delivery. In general, a message digest which is a cryptographic one way hash function containing a set of digits is used to protect the integrity of a data. The message digest is attached with the main data content and verified by the receiver, in turn it warns the receiver about the malfunctioning of payload. There are many standard algorithms exist to create the digest. This paper gives detailed review of the different algorithms suitable for XML and JSON documents and compares the performance of different algorithms.

A detailed analysis of data consistency concepts in data exchange formats (JSON & XML)

Release of a theatrical movie trailer is a major marketing practice and a considerable cost is associated with it. Evaluating the effectiveness of a theatrical movie trailer before its release could substantially contribute towards enriching its contents and economic value. The relationship between the emotional responses generated in response to a movie trailer cannot be effectively measured using traditional methods such as surveys and interviews. This paper proposes a framework to measure the effectiveness of movie trailers by measuring emotive response of viewers. A case study was conducted to study the impact of a movie trailer release on stock value of movie using virtual stock markets. Further, the case study investigated the impact of emotionally intense movie trailer over its stock price. Based on emotive content of trailers, few of the movie stocks experienced a surge of two hundred and 50 % while others experienced a marginal rise of five to 10 % only. The observed results indicated a direct relation between release of movie trailer, its emotive content and abnormal positive returns of a movie stock.

Gaurav Goyal

Papers

Use of neurometrics to choose optimal advertisement method for omnichannel business

Decoding depressive disorder using computer vision

A detailed analysis of data consistency concepts in data exchange formats (JSON & XML)

FADU-EV an automated framework for pre-release emotive analysis of theatrical trailers

Anticipating movie success through crowdsourced social media videos