What are MicroExpressions?
Micro-expressions are defined as “very brief facial expressions” that last only between one-fifteenth and one-twentieth of a second. All humans display these minuscule flashes of emotion whether or not they realize it or not and, try as they might, it is unbelievably hard to hide. The concept of ‘reading someone’s mind’ is still futuristic, but detecting micro-expressions may be the next perfect thing.
Micro-expressions became a subject of psychological interest when Ernest Haggard and Kenneth Isaacs attempted to observe non-verbal communication between therapists during their seminal 1966 study. They watched videotapes of psychotherapy sessions and found that microexpressions occurred either when patients unconsciously hid their feelings from themselves (known as repression), or when they deliberately tried to hide their feelings from others (known as suppression). While this reaction is nearly impossible to hide or control, we can identify it in other people. In fact, it’s this ability to find micro-expressions that makes it Tim Roth’s character in Lie to me very good at his job of detecting fraud.
Micro-expressions appear most repeatedly in people when they’re under stress, even though they can present themselves during a wide range of emotional responses. In 1967, Paul Ekman (a pioneer in the study of emotion and facial expressions) traveled to Papua New Guinea and found that these micro-expressions occur in precisely the same way in illiterate Fore people as they occur in people in United States of America. This means that these expressions aren’t learned, but are biologically encoded. With the help of Wallace Friesen, Paul Ekman identified seven emotions that have universal signals: fear, contempt, disgust, surprise, anger, unhappiness, and happiness.
So how do we recognize and learn microexpressions? Their brevity made them very difficult to capture with photography, so William Condon (and more recently John Gottman) decided to film the participants during their research. They then studied the footage frame by frame, noting subtle changes in appearance as microexpressions occurred. They also identified different facial traits for each emotion. Gottman then used this method to study interactions between couples. He found that, with sufficiently high accuracy, he could predict how long a couple’s relationship would last based on the micro-expressions each partner expressed during their interactions with each other.
Clearly, the ability to detect micro-expressions has profound implications with regard to everything from interviewing suspected criminals to bluffing in poker. For example, the study of microexpressions could change the nature of mental health care. In 1967 Ekman began studying fraud; analyzed clinical cases where patients attempted to hide suicidal intent by claiming they weren’t depressed. When these films are then examined in slow motion, the micro expressions that are revealed reveal strong negative feelings that the patient is trying to hide. Research by Helen Riess has shown that doctors who are better at recognizing micro-expressions in their patients are – much to their surprise – judged by their patients to be more empathetic.
Even in everyday life, the ability to recognize micro-expressions can be of great benefit to us at home and at work. It can allow for more intimate and understanding relationships with our loved ones and permit us to perform better in teams. In short, it can give us greater emotional intelligence. We’ll start noticing when our loved ones, co-workers, or customers are worried or frustrated – maybe even before they know it themselves. Beyond the realms of psychology and human relations, micro-expressions have major implications in other fields – marketing research, for example.
Companies like Emotient™ using the power of micro-expression for that exact reason. By performing facial analysis, their software is ready to detect how people react to advertisements. They can find out, for example, which demographics respond best to certain types of marketing. Maybe ultimately, advertisements will be tailor-made to individual consumers based on micro-expressions. That the company was recently purchased by Apple is a clear display of the relevance, power and importance of micro-expressions.
Perhaps the most significant development is law enforcement. It is an oversimplification to suggest that a different microexpression can indicate definite guilt, or that a certain muscle twitch means the suspect is lying. David Matsumoto explains that micro-expressions can easily indicate that there’s more to the story than is being told, and that what goes on a person’s face may not match the story they’re telling. Ekman has been working to train law enforcement in micro-expression recognition, and hopes to expand his work to the point where even malicious intent can be detected before acts of violence occur.
