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Emotion Recognition on the Basis of Peripheral Physiological Data PowerPoint Presentation
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Emotion Recognition on the Basis of Peripheral Physiological Data

Emotion Recognition on the Basis of Peripheral Physiological Data

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Emotion Recognition on the Basis of Peripheral Physiological Data

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  1. Emotion Recognition on the Basis of Peripheral Physiological Data Dipl.-Inf. David Hrabal Medizinische Psychologie Uniklinikum Ulm Ulm, 17.12.2012 Doktorandenseminar

  2. Emotion Recognition on the Basis of Peripheral Physiological Data

  3. Emotion Recognition on the Basis of Peripheral Physiological Data • What is an emotion? • What is physiological data? • Common classification methods • New approach to emotion recognition on the basis of physiological data - 'Feature-Pair Based Emotion Identification'

  4. What is an emotion?

  5. What is an emotion? • There are many definitions for “Emotion”

  6. What is an emotion? • There are many definitions for “Emotion” • It is known that emotions play a major role in: motivation, perception, cognition, coping, creativity, attention, planning, reasoning, learning, memory, decision making...

  7. What is an emotion? • There are many definitions for “Emotion” • It is known that emotions play a major role in: motivation, perception, cognition, coping, creativity, attention, planning, reasoning, learning, memory, decision making... • Like many other procedures, it consists of: sensory input (perception), action (neurological processing), output (expression)

  8. What is an emotion? • Neurophysiological action -> activation / inhibition -> changes in: heart rate, respiration frequency / intensity, temperature, muscle tension, brain wave changes

  9. What is physiological data?

  10. What is physiological data? Data that was recorded using biosensors:

  11. What is physiological data? Data that was recorded using biosensors: • EMG (electromyography)

  12. What is physiological data? Data that was recorded using biosensors: • EMG (electromyography) • SC (skin conductance)

  13. What is physiological data? Data that was recorded using biosensors: • EMG (electromyography) • SC (skin conductance) • BVP (blood volume pulse)

  14. What is physiological data? Data that was recorded using biosensors: • EMG (electromyography) • SC (skin conductance) • BVP (blood volume pulse) • Temperature • ECG (electrocardiography) • Respiration • EEG (electromyography) • ...

  15. What is an emotion? • Neurophysiological action -> activation / inhibition -> changes in: heart rate, respiration frequency / intensity, temperature, muscle tension, brain wave changes Since it is possible to measure physiological changes with biosensors and emotion leads to physiological changes, it must be possible to measure emotion with biosensors!

  16. Common Methods for Emotion Recognition Method 1: Machine Learning

  17. Common Methods for Emotion Recognition Method 1: Machine Learning selected features as inputs for an automatic classification system, a classification rate is calculated

  18. Common Methods for Emotion Recognition Method 1: Machine Learning selected features as inputs for an automatic classification system, a classification rate is calculated • From the physiological signal

  19. Common Methods for Emotion Recognition Method 1: Machine Learning selected features as inputs for an automatic classification system, a classification rate is calculated • From the physiological signal • statistical features are calculated • (extracted)

  20. Common Methods for Emotion Recognition Method 1: Machine Learning selected features as inputs for an automatic classification system, a classification rate is calculated • From the physiological signal • statistical features are calculated • (extracted) • The features are used as input • vector for a SVM or NN

  21. Common Methods for Emotion Recognition Method 1: Machine Learning selected features as inputs for an automatic classification system, a classification rate is calculated • From the physiological signal • statistical features are calculated • (extracted) • The features are used as input • vector for a SVM or NN • The classification rate is the result • of a leave-one-out classification

  22. Common Methods for Emotion Recognition Method 1: Machine Learning

  23. Common Methods for Emotion Recognition Method 1: Machine Learning

  24. Common Methods for Emotion Recognition Method 1: Machine Learning

  25. Common Methods for Emotion Recognition Method 1: Machine Learning good results in leave-one-out classification transsituational classification isn't calculated or delivers bad results

  26. Common Methods for Emotion Recognition Method 1: Machine Learning good results in leave-one-out classification transsituational classification isn't calculated or delivers bad results PROBLEM: the calculated features help specify this one recorded dataset but (in most cases) they are not transferable

  27. Common Methods for Emotion Recognition Method 2: Basic Research

  28. Common Methods for Emotion Recognition Method 2: Basic Research Individual channels are observed when trying to distignuish between emotional states like fear and sadness

  29. Common Methods for Emotion Recognition Method 2: Basic Research Individual channels are observed when trying to distignuish between emotional states like fear and sadness fear sadness

  30. Common Methods for Emotion Recognition Method 2: Basic Research - too ambiguous (mehrdeutig) : changes in a certain channel cannot be traced back to a certain emotion

  31. Common Methods for Emotion Recognition Method 2: Basic Research - too ambiguous (mehrdeutig) : changes in a certain channel cannot be traced back to a certain emotion fear sadness

  32. Common Methods for Emotion Recognition Method 2: Basic Research - too ambiguous (mehrdeutig) : changes in a certain channel cannot be traced back to a certain emotion - in this form not applicable for the basic emotion concept

  33. Common Methods for Emotion Recognition Method 2: Basic Research - too ambiguous (mehrdeutig) : changes in a certain channel cannot be traced back to a certain emotion - in this form not applicable for the basic emotion concept - what about the dimensional concept? pleasure arousal

  34. New Approach to Emotion Recognition from Physiological Data physiological channel EMG, SC or BVP

  35. New Approach to Emotion Recognition from Physiological Data physiological channel change direction EMG, SC or BVP or

  36. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2

  37. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 pleasure arousal

  38. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_corr EMG_zyg SC pleasure BVP arousal

  39. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_zyg pleasure arousal

  40. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_zyg pleasure arousal

  41. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 pleasure SC arousal

  42. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 pleasure SC arousal

  43. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_corr EMG_zyg pleasure SC BVP arousal

  44. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_corr EMG_zyg pleasure SC Each physiological parameter can affect one axis BVP arousal

  45. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2

  46. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 4

  47. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 2^2 = 4

  48. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_zyg + X 2^2 = 4

  49. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_zyg + X , , or 2^2 = 4

  50. New Approach to Emotion Recognition from Physiological Data physiological channel change direction number of states EMG, SC or BVP or 2^1 = 2 EMG_zyg + X , , or 2^2 = 4 EMG_zyg + X pleasure arousal