University Institute of Engineering & Technology

SSM-S 401 SEMINAR ON-

MIND READING COMPUTERSSUBMITTED TO-

Dr. R.N. KatiyarSeminar In-Charge

SUBMITTED BY-ANSHU MAURYACSJMA13001390005

CONTENTS INTRODUCTION PREVIOUS AND CURRENT RESEARCH OUTCOMES HOW DOES IT WORKS? TECHNIQUES ALGORITHMS AND MODELS DATABASES ADVANTAGES DISADVANTAGES AND PROBLEMS CONCLUSION REFERENCES

INTRODUCTION

People express their mental states, including emotions, thoughts and desires, all the time through facial expressions and gestures. This is true when they are interacting with machines.

Mind reading machine is co-ordination of human psychology, neuro-science and computer techniques.

Japanese scientists have discovered that the electrical activity in our brain is same when a word is spoken or left unsaid after thinking.

Scientists have identified distinct brainwaves produced for different words.

Prior knowledge of how particular mental states are expressed in the face is combined with analysis of facial expressions and head gestures occurring in real time.

Previous & Current research Outcomes

The relationship between observable head and facial displays and the corresponding hidden mental states over time is modeled.

In recent years, scientists have done tremendous jobs in decoding human thoughts. In a 2011 study, researchers translated brain waves into the movie clips people were watching at the time.

Current projects in Cambridge are considering further inputs such as body posture and gestures to improve the results.

HOW DOES IT WORKS?

Futuristic Head Band: The mind reading actually involves measuring the

volume and oxygen level of the blood around the subjects brain, using technology called functional near-infrared spectroscopy(FNIRS) which has shown 83% times accurate results.

The user wears a sort of futuristic headband that sends light rays into the tissues of the head where it is absorbed by active, blood-filled tissues.

TECHNIQUES1. Facial Affect Detection- Patterns of face and gestures are analyzed of a person.

2. Emotional Classification-Classification by Paul Ekman Anger, Fear, Happiness, Disgust ,Sadness, Surprise.

3. Facial Electromyography-It is used to measure the electrical

activity of the facial muscles. Muscles used are “corrugator supercilii muscle”

4. Galvanic Skin Response-It is a measure of skin conductivity,

which is dependent on how moist the skin is.

5. Blood Volume Pulse- It is measured by a process called photoplethysmography and it

produces a graph indicating blood flow through the extremities.

LDA (Linear Discriminant Analysis) Used in statistics, pattern recognition and machine learning to find a linear combination of features. Its time & space computation is expensive. time complexity=O(mnt+t^3), m,n are no of samples & features respectively & t=min(m,n).

k-Nearest Neighbors(k-NN) – Classify an unknown example with the most common class among k closest examples.

time complexity= O(nk+nd) , where n= no. of examples, k=closest examples, d= distance to all examples.

Hidden Markov models(HMM)- used in pattern recognition , gesture recognition.

Time complexity = O(T*N^T), where T= length of sequence, N= no of symbols .

ALGORITHMS & MODELS

SVM(Support Vector Machines)– used in statistics and machine learning to find a linear combination which decides which of the two (or more) possible classes, each input may fall into.

Its time complexity depends on techniques involved in it.

ANN(Artificial Neural Networks)-is a mathematical model, inspired by biological neural networks, that can better grasp possible non-linearities of the feature space.

Time complexity = between O(n^2) and O(n^3).

GMM(Gaussian mixture model)- is a probabilistic model used for representing the existence of sub-populations within the overall population.

Time complexity = O(kn), where n=no. of data points, k=final no. of k mixture components.

The first attempt to produce such database was the FAU Aibo Emotion Corpus for CEICES (Combining Efforts for Improving Automatic Classification of Emotional User States)

three types of databases database of peak expression images database of image sequences of emotion from neutral to its peak video clips with emotional annotations.

DATABASE

Two widely used databases CK+ and JAFFE.

Extended Cohn-Kanade (CK+)-CK was created in 2000 but was not much efficient.CK+ was created after 10 years, in whichno of img. Sequence was increased by 22%& no of subjects was increased by 27%.

Japanese Female Facial Expression(JAFFE)-it contains 213 images of 7 facial expressions of

Japanese models.

ADVANTAGES Mind-controlled wheelchair- was developed from the

University of Electro Communications in Japan.

Web Search- Search engines can detect what the user wants to browse.

e-learning applications- when a learner is bored, interested, frustrated, or pleased.

Robotic systems capable of processing information from our minds

Social monitoring- such as alerting other vehicles if it detects the driver to be angry.

Physical Disability- Affective computing is also being applied to the development of communicative technologies for use by people with autism.

military purposes, sting operations and severe investigations (as in the form of lie detector).

combined with consoles and used for mind gaming.

 

Marketing- One idea, put forth by the Romanian researcher Dr. Nicu Sebe , is the analysis of a person’s face while they are using a certain product .

  help injured astronauts control machines, or aid

disabled people.

DISADVANTAGES AND PROBLEMS

It can become a threat in privacy and can extract important and confidential information through the person.

Also these mind reading computers cannot be 100% accurate as human mind is much more complex than a computer.

If used by Sinners , can be highly dangerous.

CONCLUSION Tufts University researchers have begun a three-year

research project which, if successful, will allow computers to respond to the brain activity of the computer's user.

 Hence if we get 100% accuracy these computers may find various applications in many fields of electronics where we have very less time to react.

Due to lack of database and complexity in neuroscience a lot of more research is required in this field.

 

References- • www.newscientist.com/article/dn4795-nasa-develops-mi

ndreading-system • www.wikipedia.org

• ieeexplore.ieee.org • Hudlicka, Eva (2003). "To feel or not to feel: The role of

affect in human-computer interaction". International Journal of Human-Computer Studies

 • Cambria, Erik (2016). "Affective computing and

sentiment analysis" (PDF). IEEE Intelligent Systems.

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