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Dr. Javier Gonzalez-Sanchez [email protected] www.javiergs.info o ffi ce: 14 -227 CSC 570 Current Topics in Computer Science Applied Affective Computing Lecture 03. PAD

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Previously …

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Homework 5 A.Create your Team B.Decide what your project will be C.Start Working on a proposal ▪ What - Problem to be Address ▪ Why – Impact or Relevance ▪ How – Your product and tools to be used ▪ Have something similar been done before? ▪ Why are you different? (Google Scholar)

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Affect, Emotion, Mood 6 Label 🧪 🧪 + ⚡ ⚡ 🧪 + ⚡ Label 🧪 🧪 + ⚡ ⚡ 🧪 🧪 + ⚡ ⚡ 🧪 🧪 + ⚡ ⚡

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PAD

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Key Ideas 8 +P+A+D Engagement +P-A+D Meditation Concentration Thought Relaxation +P+A-D Excitement Interest Dependence +P-A-D Starting Agreement Docility -P+A+D Disagreement Hostility -P-A+D Disdain -P+A-D Frustration Unsureness Anxiety -P-A-D Boredom Pleasure (Valence) Arousal (Activation) Dominance

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PAD 10 Frustration - + - Hostility - + + Excitement + + - Engagement + + + Boredom - - - Disdain - - + Meditation/Concentration + - + Agreement / + - -

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(+++) Engagement (-++) Disagreement Hostility (++-) Excitement Interest Dependence (-+-) Frustration Unsureness Anxiety (+-+) Meditation Concentration Thought Relaxation (--+) Disdain (+--) Starting Agreement Docility (---) Boredom controlled In control controlled In control Aroused Aroused Pleasure Pleasure 🙂🫀🕹 🙂🫀👾 🙂 🕹 🙂 👾 Pleasure Pleasure controlled In control controlled In control Aroused Aroused 🫀🕹 🫀👾 🕹 👾

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thechalkboardmag.com 👾 🫀👾 🫀🕹 🙂🫀👾 🙂🫀🕹 🕹 👾

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SAM

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The Self-Assessment Manikin (SAM) • A pictori a l sc a le th a t me a sures ple a sure, a rous a l, a nd domin a nce • P a rticip a nts r a te their feelings by pl a cing a n X over or between f igures on the sc a le • Av a il a ble in p a per- a nd-pencil a nd computer progr a m versions • One of the most popul a r self-reporting tools in emotion rese a rch 14

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The Self-Assessment Manikin (SAM) 15

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Case Studies

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PAD 17 Hess, Thomas & Popham, Lauren & Growney, Claire. (2017). Age-Related Effects on Memory for Social Stimuli: The Role of Valence, Arousal, and Emotional Responses. Experimental Aging Research. 43. 105-123. 10.1080/0361073X.2017.1276374.

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Margaret M. Bradley, Peter J. Lang, Measuring emotion: The self-assessment manikin and the semantic differential, Journal of Behavior Therapy and Experimental Psychiatry, Volume 25, Issue 1, 1994.

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Thoughts?

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Thoughts? 20 Unsureness(-+-) Anxiety(-+-) Surprised(++-) Hostility(-++) 🙂 🙂 🙂 🫀 🫀 🫀 🫀 🫀 🫀 🫀 🕹 🕹 🙂 Concentration(+-+) Excitement(++-) Dependance(++-) Frustration (-+-) 🫀 Fear(-+-) Disdain (---)

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Thoughts? 21

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The Self-Assessment Manikin (SAM) 22

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Datasets

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From: Brain-Computer Interface (Emotiv) 24 Timestamp Short Term Excitement Long Term Excitement Engagement Meditation Frustration 101116091145065 0.447595 0.54871 0.834476 0.333844 0.536197 101116091145190 0.447595 0.54871 0.834476 0.333844 0.536197 101116091145315 0.447595 0.54871 0.834476 0.333844 0.536197 101116091145440 0.487864 0.546877 0.834146 0.339548 0.54851 101116091145565 0.487864 0.546877 0.834146 0.339548 0.54851 101116091145690 0.487864 0.546877 0.834146 0.339548 0.54851 101116091145815 0.487864 0.546877 0.834146 0.339548 0.54851 101116091145940 0.521663 0.545609 0.839321 0.348321 0.558228 101116091146065 0.521663 0.545609 0.839321 0.348321 0.558228 101116091146190 0.521663 0.545609 0.839321 0.348321 0.558228 101116091146315 0.521663 0.545609 0.839321 0.348321 0.558228 101116091146440 0.509297 0.544131 0.84401 0.358717 0.546771 101116091146565 0.509297 0.544131 0.84401 0.358717 0.546771 101116091146690 0.509297 0.544131 0.84401 0.358717 0.546771 101116091146815 0.509297 0.544131 0.84401 0.358717 0.546771 101116091146941 0.451885 0.541695 0.848087 0.368071 0.533919

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From: Face Gestures (SVM) 25 Timestamp Agreement Concentrating Disagreement Interested Thinking Unsure 101116112838516 0.001836032 0.999917 1.79E-04 0.16485406 0.57114255 0.04595062 101116112838578 0.001447654 0.9999516 1.29E-04 0.16310683 0.5958921 0.042706452 101116112838672 5.97E-04 0 1.5E-04 0.44996294 0.45527613 0.00789697 101116112838766 2.46E-04 0 1.75E-04 0.77445686 0.32144752 0.001418217 101116112838860 1.01E-04 0 2.04E-04 0.93511915 0.21167138 2.53E-04 101116112838953 4.18E-05 0 2.38E-04 0.983739 0.13208677 4.52E-05 101116112839016 1.72E-05 0 2.78E-04 0.9960774 0.07941038 8.07E-06 101116112839110 7.1E-06 0 3.24E-04 0.99906266 0.046613157 1.44E-06 101116112839156 2.92E-06 0 3.77E-04 0.99977654 0.026964737 2.57E-07 101116112839250 1.21E-06 0 4.4E-04 0.9999467 0.015464196 4.58E-08 101116112839391 4.97E-07 0 5.12E-04 0.9999873 0.008824189 8.18E-09 101116112839438 2.05E-07 0 5.97E-04 0.999997 0.005020725 1.46E-09 101116112839547 8.43E-08 0 6.96E-04 0.9999993 0.002851939 2.6E-10 101116112839578 3.47E-08 0 8.11E-04 0.9999999 0.001618473 4.64E-11 101116112839688 1.43E-08 0 9.45E-04 0.99999994 9.18E-04 8.29E-12 101116112839781 5.9E-09 0 0.001101404 1 5.21E-04 1.48E-12 101116112839828 2.43E-09 0 0.001283521 1 2.95E-04 2.64E-13

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Questions 26

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CSC 570 Applied Affective Computing Javier Gonzalez-Sanchez, Ph.D. [email protected] Spring 2025 Copyright. These slides can only be used as study material for the class CSC 570 at Cal Poly. They cannot be distributed or used for another purpose.