Forget the robot child in the movie
"AI." Vanderbilt researchers Nilanjan Sarkar and Craig Smith have a
less romantic but more practical idea in mind.
"We are not trying to give a robot emotions. We are trying to
make robots that are sensitive to our emotions," says Smith,
associate professor of psychology and human development.
Their vision, which is to create a kind of robot Friday, a
personal assistant who can accurately sense the moods of its human
bosses and respond appropriately, is described in the article,
"Online Stress Detection using Psychophysiological Signals for
Implicit Human-Robot Cooperation." The article, which appears in the
Dec. issue of the journal Robotica, also reports the initial steps
that they have taken to make their vision a reality.
"Psychological research shows that a lot of our communications,
human to human, are implicit," says Sarkar, an assistant professor
in mechanical engineering. "The better we know the other person the
better we get at understanding the psychological state of that
person. So the prime motivation of our research is to determine
whether a robot can sense the psychological state of a human person.
Sooner or later, robots will be everywhere. As they become
increasingly common, they will need to interact with humans in a
more natural fashion." When Sarkar first approached him about
collaborating on the project, Smith admits that he was very
skeptical. "I expected to listen and then explain to him why his
ideas would never work." But the engineer surprised him on two
counts: the amount he knew about the psychophysiology of emotions
and his realization that any system for detecting emotions cannot be
universal, but must be based on individual patterns.
The project has two basic parts, and both are ambitious. One is
to develop a system that can accurately detect a person's
psychological state by analyzing the output of a variety of
physiological sensors. The other is to process this information in
real time (as it happens) and convert it into a form that a computer
or robot can process.
"Psychologists have been trying to identify universal patterns of
physiological response since the turn of the century without
success. All this effort has shown is that there are no such
universal patterns," says Smith. "The hard fact is that different
individuals express the same emotion rather differently. But I think
that we have established the feasibility of the individual-specific
approach that we are taking and there is a good chance that we can
succeed," says Smith.
The Vanderbilt researchers are using an approach similar to that
adopted by voice and handwriting recognition systems. They are
gathering baseline information about each person and analyzing it to
identify the responses associated with different mental states. One
advantage that the researchers have is the recent advances in sensor
technology. "Extremely small, 'wearable' sensors have been developed
that are quite comfortable and are fast enough for real-time
applications," says Sarkar.
Their first experiments concentrated on detecting high and low
anxiety levels using a heart rate monitor. "There are sophisticated
medical diagnostic techniques that can detect stress in a patient,"
they acknowledge in their Robotica paper, but add, "All those
techniques are slow, expensive and, more importantly, not suitable
for a person who is moving and working."
In this case the researchers used playing video games to put
subjects under pressure and induce stress. By varying the level of
difficulty of the games, they were able to vary the level of stress
involved. They obtained electrocardiogram data from several
video-gaming playing subjects over a six-month period.
Sarkar and his research team used advanced signal processing
techniques, including wavelet analysis and fuzzy logic, to analyze
the heart-rate data. They looked specifically at variations in the
interval between heartbeats, a common measure of heart rate
variability. They identified two frequency bands that vary
predictably with changes in stress levels. These bands are
associated with the parasympathetic and sympathetic divisions of the
autonomic nervous system. The parasympathetic system reduces heart
rate and tends to control heart rate under most normal conditions.
The sympathetic system responds to fear and excitement and tends to
increase heart rate during emergency situations.
"In all the experiments we conducted, we found that, when a
subject became stressed, the level of sympathetic activity increased
and level of parasympathetic activity decreased," Sarkar says.
He and his research team have since supplemented their measures
of heart rate with measures of skin conductance (affected by
variations hand sweating) and facial muscle activity (brow furrowing
and jaw clenching). They were able to combine this information to
produce a series of rules that allow a robot to respond to
information about a person's emotional state. They have used these
to program a small mobile robot. The robot is initially given a task
of exploring the room. So it begins moving randomly about on the
floor. Then physiological data of a person experiencing high anxiety
levels is sent to a processor that detects the anxiety level and
instructs the mobile robot to move to a specific location and say,
"I sense that you are anxious. Is there anything I can do to help?"
In order to investigate additional psychological states, Smith
has created three simple tasks – anagram, sound discrimination and
math problems that systematically increase difficulty – that are
designed specifically to make the performer frustrated or bored.
They will be adding additional sensors, such as electroencephalogram
(EEG) brain wave monitors and additional measures of cardiovascular
activity. The next challenge that the researchers face is finding a
way to discriminate between high levels of anxiety and engagement.
These two states are accompanied by physiological responses that are
much closer to each other than either of them are to low levels of
anxiety or engagement. "This is the really big one," says Smith.
The research is supported by grants from the National Science
Foundation, the NASA Institute for Advanced Concepts and Vanderbilt
University.
Note: This story has been adapted from a
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If you wish to quote any part of this story, please credit
Vanderbilt University as the original source. You may also
wish to include the following link in any citation:
http://www.sciencedaily.com/releases/2002/12/021216070618.htm