Affective Medicine: a review of Affective Computing efforts in Medical Informatics

Background: Affective computing (AC) is concerned with emotional interactions performed with and through computers. It is defined as “computing that relates to, arises from, or deliberately influences emotions”. AC enables investigation and understanding of the relation between human emotions and health as well as application of assistive and useful technologies in the medical domain. Objectives: 1) To review the general state of the art in AC and its applications in medicine, and 2) to establish synergies between the research communities of AC and medical informatics. Methods: Aspects related to the human affective state as a determinant of the human health are discussed, coupled with an illustration of significant AC research and related literature output. Moreover, affective communication channels are described and their range of application fields is explored through illustrative examples. Results: The presented conferences, European research projects and research publications illustrate the recent increase of interest in the AC area by the medical community. Tele-home healthcare, AmI, ubiquitous monitoring, e-learning and virtual communities with emotionally expressive characters for elderly or impaired people are few areas where the potential of AC has been realized and applications have emerged. Conclusions: A number of gaps can potentially be overcome through the synergy of AC and medical informatics. The application of AC technologies parallels the advancement of the existing state of the art and the introduction of new methods. The amount of work and projects reviewed in this paper witness an ambitious and optimistic synergetic future of the affective medicine field

Crowdsourcing a Word-Emotion Association Lexicon

Even though considerable attention has been given to the polarity of words (positive and negative) and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited and small emotion lexicons. In this paper we show how the combined strength and wisdom of the crowds can be used to generate a large, high-quality, word-emotion and word-polarity association lexicon quickly and inexpensively. We enumerate the challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them. Most notably, in addition to questions about emotions associated with terms, we show how the inclusion of a word choice question can discourage malicious data entry, help identify instances where the annotator may not be familiar with the target term (allowing us to reject such annotations), and help obtain annotations at sense level (rather than at word level). We conducted experiments on how to formulate the emotion-annotation questions, and show that asking if a term is associated with an emotion leads to markedly higher inter-annotator agreement than that obtained by asking if a term evokes an emotion

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Emotion Recognition using Fuzzy K-Means from Oriya Speech

Communication will be intelligible when conveyed message is interpreted in right-minded. Unfortunately, the rightminded interpretation of communicated message is possible for human-human communication but it’s laborious for humanmachine communication. It is due to the inherently blending of non-verbal contents such as emotion in vocal communication which leads to difficulty in human-machine interaction. In this research paper we have performed experiment to recognize emotions like anger, sadness, astonish, fear, happiness and neutral using fuzzy K-Means algorithm from Oriya elicited speech collected from 35 Oriya speaking people aged between 22- 58 years belonging to different provinces of Orissa. We have achieved the accuracy of 65.16% in recognizing above six mentioned emotions by incorporating mean pitch, first two formants, jitter, shimmer and energy as feature vectors for this research work. Emotion recognition has many vivid applications in different domains like call centers, spoken tutoring systems, spoken dialogue research, human-robotic interfaces etc

Когнитивни процеси, емоции и интелигентни интерфејси

Студијата презентира истражувања од повеќе научни дисциплини, како вештачка интелигенција, невронауки, психологија, лингвистика и филозофија, кои имаат потенцијал за креирање на интелигентни антропоморфни агенти и интерактивни технологии. Се разгледуваат системите од симболичка и конекционистичка вештачка интелигенција за моделирање на човековите когнитивни процеси, мислење, донесување одлуки, меморија и учење. Се анализираат моделите во вештачка интелигенција и роботика кои користат емоции како механизам за контрола на остварување на целите на роботот, како реакција на одредени ситуации, за одржување на процесот на социјална интеракција и за создавање на поуверливи антропормфни агенти. Презентираните интердисциплинарни методологии и концепти се мотивација за создавање на анимирани агенти кои користат говор, гестови, интонација и други невербални модалитети при конверзација со корисниците во интелигентните интерфејси

VICA, a visual counseling agent for emotional distress

We present VICA, a Visual Counseling Agent designed to create an engaging multimedia face-to-face interaction. VICA is a human-friendly agent equipped with high-performance voice conversation designed to help psychologically stressed users, to offload their emotional burden. Such users specifically include non-computer-savvy elderly persons or clients. Our agent builds replies exploiting interlocutor\u2019s utterances expressing such as wishes, obstacles, emotions, etc. Statements asking for confirmation, details, emotional summary, or relations among such expressions are added to the utterances. We claim that VICA is suitable for positive counseling scenarios where multimedia specifically high-performance voice communication is instrumental for even the old or digital divided users to continue dialogue towards their self-awareness. To prove this claim, VICA\u2019s effect is evaluated with respect to a previous text-based counseling agent CRECA and ELIZA including its successors. An experiment involving 14 subjects shows VICA effects as follows: (i) the dialogue continuation (CPS: Conversation-turns Per Session) of VICA for the older half (age > 40) substantially improved 53% to CRECA and 71% to ELIZA. (ii) VICA\u2019s capability to foster peace of mind and other positive feelings was assessed with a very high score of 5 or 6 mostly, out of 7 stages of the Likert scale, again by the older. Compared on average, such capability of VICA for the older is 5.14 while CRECA (all subjects are young students, age < 25) is 4.50, ELIZA is 3.50, and the best of ELIZA\u2019s successors for the older (> 25) is 4.41