The way a person moves their hands and legs while walking can reveal clues to how they are feeling, scientists discover in a new study.
Humans draw on a range of cues about other people to “read” their internal emotional state.
These cues can include micro-expressions, such as subtle movement of the eyebrows, eyes, and mouth, which can signal happiness, anger, fear, sadness, and surprise.
Subtle changes in one’s body language from an open to a closed posture can also reveal if the person is showing interest or feeling stressed.
While in our daily lives such cues help infer someone’s mood, how exactly specific movement patterns signal distinct emotions remains elusive.
Now, researchers have found that the way one swings their arms and legs is connected to specific emotions.
In the new study, scientists aimed to identify and manipulate movement patterns in gait and determine how they influence emotion recognition.
They found that people could judge someone’s emotions from a motion capture video.
In one experiment, participants assessed videos of trained actors’ coordinated movement patterns and deduced their emotional state.
The actors were instructed to recall personal life events that provoked anger, happiness, fear or sadness before they walked a short distance while dwelling on the memory.
They also wore reflective markers, which allowed scientists to create point-light videos.
Another experiment varied people’s gait with emotion to resemble angry, sad, and fearful states.
Scientists found that the participants’ emotion judgments shifted significantly in the predicted direction.
Participants were able to infer the actors’ emotions at a better than level of chance, according to the study.
Larger arm movements were perceived to be linked with anger, while reduced movements were associated with sadness, researchers say.
The findings indicate that specific movement patterns can independently influence emotion recognition.
“To some degree, the walkers’ intended emotions were indeed perceived by the observers,” scientists wrote in the study published in the journal Royal Society Open Science.
“Our approach offers an effective framework for isolating and manipulating dynamic features within complex movements, thereby advancing understanding of emotional, aesthetic, and technical evaluations of movement,” they wrote.
