[humanser] FACIAL EXPRESSION - IS IT RELIABLE?

[JD Townsend]

New York Times Science Desk Section 2014 March 29


A Truth-Teller for Fake Pain.  By JAN HOFFMAN.  How well can
computers interact with humans? Certainly computers play a mean
game of chess, which requires strategy and logic, and 'Jeopardy!
,' in which they must process language to understand the clues
read by Alex Trebek (and buzz in with the correct question).
But in recent years, scientists have striven for an even more
complex goal: programming computers to read human facial
expressions..
The practical applications could be profound.  Computers could
supplement or even replace lie detectors.  They could be
installed at border crossings and airport security checks.  They
could serve as diagnostic aids for doctors.
Researchers at the University of California, San Diego, have
written software that not only detected whether a person's face
revealed genuine or faked pain, but did so far more accurately
than human observers.
While other scientists have already refined a computer's ability
to identify nuances of smiles and grimaces, this may be the first
time a computer has triumphed over humans at reading their own
species.
'A particular success like this has been elusive,' said Matthew
A.  Turk, a professor of computer science at the University of
California, Santa Barbara.  'It's one of several recent examples
of how the field is now producing useful technologies rather than
research that only stays in the lab.  We're affecting the real
world.
People generally excel at using nonverbal cues, including facial
expressions, to deceive others (hence the poker face).  They are
good at mimicking pain, instinctively knowing how to contort
their features to convey physical discomfort.
And other people, studies show, typically do poorly at detecting
those deceptions.
In a recent study in Current Biology by researchers at San Diego,
the University of Toronto and the State University of New York at
Buffalo, humans and a computer were shown videos of people in
real pain or pretending.  The computer differentiated suffering
from faking with greater accuracy by tracking subtle muscle
movement patterns in the subjects' faces.
'We have a fair amount of evidence to show that humans are paying
attention to the wrong cues,' said Marian S.  Bartlett, a
research professor at the Institute for Neural Computation at San
Diego and the lead author of the study.
For the study, researchers used a standard protocol to produce
pain, with individuals plunging an arm in ice water for a minute
(the pain is immediate and genuine but neither harmful nor
protracted).  Researchers also asked the subjects to dip an arm
in warm water for a moment and to fake an expression of pain.
Observers watched one-minute silent videos of those faces, trying
to identify who was in pain and who was pretending.  Only about
half the answers were correct, a rate comparable to guessing.
Then researchers provided an hour of training to a new group of
observers.  They were shown videos, asked to guess who was really
in pain, and told immediately whom they had identified correctly.
Then the observers were shown more videos and again asked to
judge.  But the training made little difference: The rate of
accuracy scarcely improved, to 55 percent.
Then a computer took on the challenge.  Using a program that the
San Diego researchers have named CERT, for computer expression
recognition toolbox, it measured the presence, absence and
frequency of 20 facial muscle movements in each of the 1,800
frames of one-minute videos.  The computer assessed the same 50
videos that had been shown to the original, untrained human
observers.
The computer learned to identify cues that were so small and
swift that they eluded the human eye.  Although the same muscles
were often engaged by fakers and those in real pain, the computer
could detect speed, smoothness and duration of the muscle
contractions that pointed toward or away from deception.  When
the person was experiencing real pain, for instance, the length
of time the mouth was open varied; when the person faked pain,
the time the mouth opened was regular and consistent.  Other
combinations of muscle movements were the furrowing between
eyebrows, the tightening of the orbital muscles around the eyes,
and the deepening of the furrows on either side of the nose.
The computer's accuracy: about 85 percent.
Jeffrey Cohn, a University of Pittsburgh professor of psychology
who also conducts research on computers and facial expressions,
said the CERT study addressed 'an important problem, medically
and socially,' referring to the difficulty of assessing patients
who claim to be in pain.  But he noted that the study's observers
were university students, not pain specialists.
Dr.  Bartlett said she didn't mean to imply that doctors or
nurses do not perceive pain accurately.  But 'we shouldn't assume
human perception is better than it is,' she said.  'There are
signals in nonverbal behavior that our perceptual system may not
detect or we don't attend to them.
Dr.  Turk said that among the study's limitations were that all
the faces had the same frontal view and lighting.  'No one is
wearing sunglasses or hasn't shaved for five days,' he said.
Dr.  Bartlett and Dr.  Cohn are working on applying facial
expression technology to health care.  Dr.  Bartlett is working
with a San Diego hospital to refine a program that will detect
pain intensity in children.
'Kids don't realize they can ask for pain medication, and the
younger ones can't communicate,' she said.  A child could sit in
front of a computer camera, she said, referring to a current
project, and 'the computer could sample the child's facial
expression and get estimates of pain.  The prognosis is better
for the patient if the pain is managed well and early.
Dr.  Cohn noted that his colleagues have been working with the
University of Pittsburgh Medical Center's psychiatry department,
focusing on severe depression.  One project is for a computer to
identify changing patterns in vocal sounds and facial expressions
throughout a patient's therapy as an objective aid to the
therapist.
'We have found that depression in the facial muscles serves the
function of keeping others away, of signaling, 'Leave me alone,'
' Dr.  Cohn said.  The tight-lipped smiles of the severely
depressed, he said, were tinged with contempt or disgust, keeping
others at bay.
'As they become less depressed, their faces show more sadness,'
he said.  Those expressions reveal that the patient is implicitly
asking for solace and help, he added.  That is one way the
computer can signal to the therapist that the patient is getting
better..  PHOTOS: Can you tell which expressions show real pain
and which ones are feigned? A study found that human  observers
had no better than a 55 percent rate of success, even with
training, while a computer  was accurate about 85 percent of the
time.  
JD Townsend, LCSW


JD Townsend LCSW
Helping the light dependent to see.
Daytona Beach, Earth, Sol System
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