:-)

1. EMOTION RECOGNITION USING SMARTPHONES
-Madhusudhan (17)

2. OBJECTIVE
• To propose the development of android applications
that can be used for sensing the emotions of people
for their better health.
• To provide better services and also better Human-machine
interactions

3. INTRODUCTION
• Emotions control your thinking, behavior and
actions.
• Emotions affect your physical bodies as much as
your body affects your feelings and thinking.
• People who ignore, dismiss or repress their
emotions, are setting themselves up for physical
illness.

5. DETECTION
• Detection of emotional info can be done with
passive sensors which capture data about the user's
physical state or behavior without interpreting the
input.
• A video camera might capture facial expressions,
body posture and gestures.
• A microphone can capture speech.

6. • A pressure sensor/accelerometer can capture heart
rate.
• Other sensors detect emotional cues from skin
temperature.

7. RECOGNIZING
• Extraction of information for meaningful patterns
from the gathered data
• Speech recognition, natural language processing,
or facial expression detection
• These techniques should either produce labels or
efficient inference algorithms to extract high-level
information from the data.

8. SPEECH
• Requires the creation of a reliable database
or knowledge base as well as the selection of a
successful classifier which will allow for quick and
accurate emotion identification.
• Currently, the most frequently used classifiers are
linear discriminant classifiers (LDC), k-nearest
neighbour (k-NN), Gaussian mixture model (GMM),
support vector machines (SVM), artificial neural
networks (ANN), decision tree algorithms and
hidden Markov models (HMMs).

9. FACIAL EXPRESSIONS
• Defining expressions in terms of muscle actions A
system has been conceived in order to formally
categorize the physical expression of emotions.
• By studying the contraction or a relaxation of one or
more muscles.
• The concept of the Facial Action Coding System, or
FACS created by Paul Ekman and Wallace V.
Friesen in 1978
• Eg. Affdex

10. • By identifying different
facial cues, scientists are
able to map them to their
corresponding Action Unit
code
• They have proposed the
following classification of
the six basic emotions,
according to their Action
Units
Emotion Action Units
Happiness 6+12
Sadness 1+4+15
Surprise 1+2+5B+26
Fear
1+2+4+5+20+2
6
Anger 4+5+7+23
Disgust 9+15+16
Contempt R12A+R14A

11. HEART BEAT
• One of the most commonly used techniques is by
using pressure sensors/accelerometer.
• The heart rate can also be collected using the Optical
pulse sensor Eg. Samsung galaxy S5.
• Heart Rate Variability (HRV) signals is derived from
ECG signals through QRS detection algorithm.

12. • It is used as a statistical feature to distinguish the
emotional stress, through a nonlinear classifier (K
Nearest Neighbor (KNN))into three different classes
namely, negative emotions, positive emotions
(surprise and happy) and neutral.

13. CONCLUSION
• To understand the emotions with the help of
smartphones will help in achieving greater success
in the lives of people.
• Using smartphones to do this will make it much
more easier for researchers and scientists.

14. REFERENCES
• http://www.mkprojects.com/fa_emotions.html by By Mary
Kurus
• Emotion Recognition from Speech by Ankur Sapra, Nikhil
Panwar, Sohan Panwar -Jaypee Institute of Information
Technology, Noida
• http://en.wikipedia.org/wiki/Affective_computing#Emotional_s
peech
• Mobile Sensor Data Collector using Android Smartphone by
Won-Jae Yi, Weidi Jia, and Jafar Saniie - Department of
Electrical and Computer Engineering, Illinois Institute of
Technology
• EmotionSense: A Mobile Phones based Adaptive Platform for
Experimental Social Psychology Research

15. THANK YOU