1. Affective Computing Multimedia Communications University of Ottawa Ana Laura Pérez Rocha Anwar Fallatah

2. Content: Definition of Affective Computing Emotion Classification Functions Sciences and Fields of Study involved Technologies Applications

3. Origin: The Affective Computing was developed by Rosalind Picard (1995) from MIT as a tool to improve the interface man- machine by including affective connotations. All this to improve the computer’s performance and user’s productivity as well.

4. DEFINITION Affective Computing is a field of study based on how to create systems and devices that are able to recognize, interpret and simulate human emotions. Source: Google Images

5. Sciences and Fields of Study Involved There are four fields of study involved in the development of affective computing: - Computer Science - Electrical Engineering - Psychology - Biology

6. Computer Science It is the study which deals with software development to process collected data. Electrical Engineering It is a field of engineering, which allows us to develop digital models which deals with the collection of data from human, making use of sensors and smart devices.

7. Psychology This is the science that involves the study of human emotions and reactions. Biology This science studies human organs and how we can detect emotions from them. Examples: - Heart rate. - Muscular Tension.

8. Emotions Since emotions are the key issue in affective computing we need to define and classify emotions. What are emotions? Are the response to the different situations we experiment in our environment and they play an important role in the decision-making process and solving problems as well. Emotions have two components: 1. Mental component (cognitive) 2. Physical component (body)

9. Classification of emotions EMOTIONS PRIMARY SECONDARY Occurred as a direct consequence of encountering some kind of event. Cause a detectable physical response in the body: Fear a heightened heartbeat, increased “flinch” response, and increased and muscle tension. Anger based on sensation, seems indistinguishable from fear. Happiness is often felt as an expansive or swelling feeling in the chest and the sensation of lightness or buoyancy, Sadness feeling of tightness in the throat and eyes, and relaxation in the arms and legs. Shame can be felt as heat in the upper chest and face. Desire can be accompanied by a dry throat, heavy breathing, and increased heart rate. Can be caused directly by primary emotions or come from a cognitive process Antonio Damasio (1994) ex. Embarrassment

10. Functions For a Computer to be Affective should have at least one of the following functions:  Recognizing Emotion.  Expressing Emotion.  Having Emotion.

11. Functions  Recognizing Emotion. http://poseidon.csd.auth.gr/LAB_RESEARCH/Latest/imgs/HCI_img3

12. Functions  Expressing Emotion. http://www.takanishi.mech.waseda.ac.jp/top/research/eyes/we-4rII/index.htm

13. Functions  Having Emotion. Affective Computing Vs Artificial Intelligence

14. How can emotions be recognized? For a computer to be Affective should be able to get information from the human body, considering: Physical Aspects: facial expressions, voice intonation, gestures, movements… Physiological Aspects: respiration, heart rate, pulse, blood pressure, temperature, pupillary dilation, skin color….

15. Diagram of affective computing Emotions The user Devices Attached Interaction of Affective computing Sensing Detecting Interpreting Recognizing Understanding Processing Affective communication http://www.scholarpedia.org/article/Affective_computing

16. Sensors They provide all the information about the user´s physiological state. Some of these sensors are: The Galvanic Skin Response (GSR) Sensor The Blood Volume Pulse Sensor The Respiration Sensor The Electromyogram (EMG) Sensor (measures the activity of the muscles) TECHNOLOGIES

17. The prototypical sensing system Source-http://affect.media.mit.edu/areas.php?id=sensing (28/10/10)

18. Blue Eyes Technology This sensing technology makes use of most modern cameras and microphones to identify users actions. “The machine can understand what a user wants, where he is looking at, and even realize his physical or emotional states” THE TERM BLUE EYES BLUE in the term stands for Bluetooth, which enables reliable wireless communication. EYES, because the eye movement enables us to obtain a lot of interesting and important information. (Team of Poznan University of Technology, CSIDC,2001)

19. Facial Expression Recognition Basic facial expressions are: neutral, anger, sadness, surprise, happiness, disgust, fear [P. Ekman & W. Friesen, 1976] http://sciyo.com/articles/show/title/facial_expression_recognition_using_3d_facial_feature_distances

20. Basic Architecture of Facial Expression Recognition System http://sciyo.com/articles/show/title/facial_expression_recognition_using_3d_facial_feature_distances

21. Affective Haptics Area of research focus on develop devices and systems to provoke emotions by the sense of touch, some of them are: Haptiheart HaptiHug HaptiTickler HaptiButterfly Affective Haptic Devices worn on a human body Source-Tsetserukou, Dzmitry; Alena Neviarouskaya, Helmut Prendinger, Naoki Kawakami, Susumu Tachi (2009) Computing and Intelligent Interaction (ACII'09), Amsterdam, the Netherlands, IEEE Press. pp. 181–186.

22. Applications We can classify applications of affective computing into four categories mainly, which are: ◦ Security. ◦ Education. ◦ Health and Medicine. ◦ Military. ◦ Home

23. Applications  Security : Emotions can be reliable in term of security. Examples: 1. Smart Cameras. 2. Lie detectors. 3. Emotional Speech processing.

24. Applications  Education : Knowing the emotional feedback of learners enhance teaching styles. Examples: 1. Electronic Tutoring. 2. E-Learning. 3. Affective mirror. 4. Text-to-speech applications.

25. Applications  Health and Medicine : Knowing the emotions of patients helps in the treatment. Examples: 1. Measuring the affects of medicines. 2. Helping people with mental Illness. 3. Affective mirror.

26. Applications  Military : To have devices with emotional intelligence. Examples: 1. Training equipment. 2. Simulation systems.

27. Applications  Home : To have devices with emotional intelligence. Examples: 1. Video Games. 2. Delivering emotions in communication. 3. Toys.

28. Vision Some applications of the affective computing make use of sensors located on the computer’s keyboard and mouse in order to detect user’s signals and emotions. With this information, and making use of the color psychology (which is still a young field of study of the effects of colors in people’s perception and behaviour) the computer can change the color of applications that could help the user to improve or to keep his/her mood. This could be applied in offices, schools, e-learning apps…

29. Vision Affective Smart Homes, this could be a future home application. Using a camera to recognize face and facial expressions to identify the person that comes into the house and his/her emotions. When the person comes in, the computer could play a greeting sound and according to the person’s answer, recognize emotions through the voice intonation. Sending this information to the computer and after the analyses of the data, create a favorable environment for the user by sending signals to different actuators around the smart home

30. Vision Another field of study could be included in the Affective Computing research, such as Sociology, which study the one’s behaviour in all types of social groups or activities. This will allow researchers to create applications not just for help one person but to help a group of people.

31. Conclusions Affective Computing is a relative young field of study, and it promises a great development, from very simple or basic to more complex applications, such as the attention to people with disabilities, robotics with affective characteristics that promises a wide range of home, industry and health applications, to name a few.

32. Conclusions Counting on a computer that has the ability to understand and express its own emotions, while recognizing the emotions in people and then, using them to motivate adaptive behaviors can be very positive for cognitive and learning purposes or for medicine applications, such as the several types of therapies (physical and psychological).

33. Conclusions It would be interesting to know the potential market for a particular tool or application of the affective computing and how many people own a computer that meets the minimum requirements for the implementation of an affective computer and on this basis develop strategies to open or to expand this potential market since most of the applications have been developed just for research purposes.

34. THANK YOU!!!

35. References Picard, R.(1997). ‘Affective Computing’ London, MIT Press, 22,23,26,27,29,90-100. Wikidoc, Emotions, http//www.wikidoc.org/index.php/Emotional (accessed 27/10/2010). Soyel, H. and Demirel, H (2008). Facial Expression Recognition using 3D Facial Feature Distance: Affective Computing, Austria: Intech, 2,8. Tsetserukou, Dzmitry; Alena Neviarouskaya, Helmut Prendinger, Naoki Kawakami, Mitsuru Ishizuka, Susumu Tachi (2009). Enhancing Mediated Interpersonal Communication through Affective Haptics. in Proc. 3rd Int. Conf. on Intelligent Technologies for Interactive Entertainment (INTETAIN'09), Amsterdam, the Netherlands, Springer, Volume 9, Part 3. pp. 246–251. AllA Laboratory, Computer Vision and Image Processing Group, http://poseidon.csd.auth.gr/LAB_RESEARCH/Latest/AffectRecognition.htm#Item1 (accessed 21/10/2010) http://poseidon.csd.auth.gr/LAB_RESEARCH/Latest/AffectRecognition.htm#Item1 MIT MediaLab: Affective Computing Group, webpage: http://affect.media.mit.edu/areas.php?id=sensing (accessed 28/10/2010) http://affect.media.mit.edu/areas.php?id=sensing Seminar on Blue Eyes Technology, http://www.scribd.com/doc/20922174/Blue-Eyes- Technology (accessed 28/10/2010)http://www.scribd.com/doc/20922174/Blue-Eyes- Technology Scholarpedia, Affective Computing, http://www.scholarpedia.org/article/Affective_computing (accessed 21/10/2010) http://www.scholarpedia.org/article/Affective_computing Google images