Perceiving and deciphering is a vital part of social interaction. While we comprehend the spatial qualities of an expression — how the mouth moves in a smile, for example — the speeds at which expressions are produced are often overlooked.
The ability to get on and quickly decipher these signs could likewise assist individuals with deciding facial expressions even when mask-wearing might limit other visual cues.
A recent study quantified the speed of changes in distance between key facial expressions. Conducted by the University of Birmingham, scientists found that people tend to produce happy and angry expressions more rapidly, while sad expressions are made more slowly.
Lead author Dr. Sophie Sowden said, “Better understanding how people interpret this important visual cue could give us new insights into the diagnosis of conditions such as Autism Spectrum Disorder or Parkinson’s Disease. This is because patients with these conditions often recognize facial expressions differently, or exhibit expressions differently.”
In the examination, people were asked to generate facial expressions directed at a camera. They used an open-source programming program called OpenFace to track their facial movement. They estimated the speed of movement in regions of the face known to be significant in producing expression, including around the eyebrows, the nose, and the mouth, just as across the face in general.
During the first part of the experiment, scientists studied the average speed at which participants produced different expressions. In this part, participants were asked to produce ‘posed expressions,’ as well as expressions during the speech, and spontaneous expressions were recorded in response to emotion-inducing videos. Interestingly, they showed differences in speed across emotions depends on the region of the face and the ‘type’ of expression being considered.
In a second phase of the study, the team investigated what would happen if they captured schematic versions of facial expressions produced and manipulated the speeds involved. In this experiment, the scientists found that people would get better at recognizing it as happy or angry as the expression was speeded up. In contrast, if it were slowed down, people would more accurately identify it as sad.
Scientists believe that this study could pave the way towards diagnosing autism and Parkinson’s disease. It could also be useful in a range of artificial intelligence applications such as facial recognition software.
Journal Reference:
- Sophie Sowden et al. The role of movement kinematics in facial emotion expression production and recognition. Emotion, 2021; DOI: 10.1037/emo0000835