Facial expressions are formed by the movement of 43
facial muscles, which are almost entirely innervated by the facial nerve, aka the seventh
cranial nerve. These muscles are attached to either a bone and facial tissue or just facial tissue.
Facial expressions can appear intentionally or actively, as when putting on a forced smile,
or involuntarily, for instance, laughing at a clown.
The facial nerve, which emerges from the brainstem, controls involuntary and spontaneous
expressions. Intentional facial expressions on the other hand, are controlled by a different part of the
brain, the motor cortex. This is why a fake smile does not appear or feel the same as a genuine smile,
it does not reach the eyes.
Facial expressions can be categorized into three types: macro expressions, micro expressions
and subtle expressions. Macro expressions last up to 4 seconds and are obvious to the naked eye. Micro
expressions, on the other hand, last only a fraction of a second, and are harder to detect. They appear
when the subject is either deliberately or unconsciously concealing a feeling.
Subtle expressions are associated with the intensity of the emotion, not the duration. They
emerge either at the onset of an emotion, or when the emotional response is of low intensity.
While facial coding can detect macro expressions, it is unable to capture finer micro expressions
or the subtle facial expressions where the underlying musculature is not active enough to move the skin.
An alternative technique, Facial Electromyography (fEMG), can detect these finer movements by
measuring the activation of individual muscles. It has much higher temporal resolution, which makes it
ideal for recording subtle, fleeting expressions. However, since it is not practical to place more than one or
two electrodes on the face, the range of expressions fEMG can track is limited. The additional hardware
also makes it much less versatile than facial coding, for large scale consumer research studies.
