[humanser] FACIAL EXPRESSION - IS IT RELIABLE?

[Dr. Chappell]

JD,
Thanks for this fascinating  article. It will offer me true fodder in my
work in pain management and great space for exploration with my depressed
patients. Thank you.
Mary Tatum Chappell, Psy. D.

-----Original Message-----
From: humanser [mailto:humanser-bounces at nfbnet.org] On Behalf Of JD Townsend
Sent: Tuesday, May 06, 2014 10:32 PM
To: Human Services Mailing List
Subject: [humanser] FACIAL EXPRESSION - IS IT RELIABLE?


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