FaceReader customer success stories
Studying user behavior and interactions
Researchers at the Social Media Lab analyze how users interact with social media.
Learn what your users need
This type of research helps civil society organisations and other professionals to identify their customers' needs and implement new tools.
Efficient coding of social behavior
At the Social Behavior Lab at Western University, dr. Erin Heerey explores human behavior during social interactions.
Save hours of manual coding
Frame-by-frame expression analysis of her project would have taken 800 hours of manual coding. FaceReaderTM did it in only 14 hours!
The role of sensory evaluation
At Virginia Tech Food Science & Technology, researchers use FaceReader to capture how people are responding to food products.
Observe unconscious responses
Studying unconscious responses helps researchers to gain insight in the effects of flavor, sensory quality, and nutrient value of food.
FaceReader webinars
The psychophysiology of emotion
In this webinar, you'll learn about the relationship between emotional states and psychophysiological measures.
- Discover how evolution shaped our brains
- Learn how to measure heart rate and skin conductance
- Observe patterns in physiological responses to certain emotions
Reading materials
FaceReader methodology
Learn more about how FaceReader classifies facial expressions.
You'll also discover what types of data you can collect for your research and how the software is validated.
Facial Action Coding System
The Facial Action Coding System (FACS) was developed by Ekman.
This model describes different Action Units - the smallest visible units of muscular activity in the face.
Custom expressions
In FaceReader, you can combine different metrics to create your own expressions.
Learn how to create custom expressions and get inspired by examples from other researchers.
FaceReader Online
Looking for a way to study participants remotely, from any location?
Discover the benefits of FaceReader Online and read about best practices when designing your study.
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Featured blog posts
How emotions are made
Neuroscience research shows that emotions are created in our brains.
It's how our brains give meaning to our experiences and sensations. Learn more in this blog post.
5 tips to optimize your facial expression analyses
Emotion data allows researchers to gain in-depth insights in complex human behaviors.
These 5 tips will guarantee the best results in your facial expression analysis!
Using Baby FaceReader for automated analysis of infant emotions
What if you had a way to understand a baby's unspoken needs?
This study highlights to benefits of analyzing facial expressions in infants.
Facial Action Units
Below you can see the 20 Action Units offered in FaceReader as well as some frequently occurring or difficult Action Unit combinations.
Some images have been zoomed in on the area of interest to explicitly show what muscle movement corresponds to the specific Action Unit.
AU 1. Inner Brow Raiser
Contributes to sadness, surprise, and fear. Muscular basis: frontalis (pars medialis).
AU 2. Outer Brow Raiser
Contributes to surprise and fear. Muscular basis: frontalis (pars lateralis).
AU 4. Brow Lowerer
Contributes to sadness, fear, and anger. Muscular basis: depressor glabellae, depressor supercilii, corrugator supercilii.
AU 5. Upper Lid Raiser
Contributes to surprise, fear, and anger. Muscular basis: levator palpebrae superioris, superior tarsal muscle.
AU 6. Cheek Raiser
Contributes to happiness. Muscular basis: orbicularis oculi (pars orbitalis).
AU 7. Lid Tightener
Contributes to fear and anger. Muscular basis: orbicularis oculi (pars palpebralis).
AU 9. Nose Wrinkler
Contributes to disgust. Muscular basis: levator labii superioris alaeque nasi.
AU 10. Upper Lip Raiser
Muscular basis: levator labii superioris, caput infraorbitalis.
AU 12. Lip Corner Puller
Contributes to happiness and contempt. Muscular basis: zygomaticus major.
AU 14. Dimpler
Contributes to contempt and boredom. Muscular basis: buccinator.
AU 15. Lip Corner Depressor
Contributes to sadness and disgust. Muscular basis: depressor anguli oris.
AU 17. Chin Raiser
This Action Unit contributes to the affective attitudes interest and confusion. The underlying facial muscle is mentalis.
AU 18. Lip Pucker
The underlying facial muscles are incisivii labii superioris and incisivii labii inferioris.
AU 20. Lip Stretcher
Contributes to the emotion fear. The underlying facial muscle is risorius w/ platysma.
AU 23. Lip Tightener
Contributes to the emotion anger, and to the affective attitudes confusion and boredom. Muscular basis: orbicularis oris.
AU 24. Lip Pressor
This Action Unit contributes to the affective attitude boredom. The underlying facial muscle is orbicularis oris.
AU 25. Lips Part
The muscular basis consists of depressor labii inferioris, or relaxation of mentalis or orbicularis oris.
AU 26. Jaw Drop
Contributes to the emotions surprise and fear. Muscular basis: masseter; relaxed temporalis and internal pterygoid.
AU 27. Mouth Stretch
The underlying facial muscles are pterygoids and digastric.
AU 43. Eyes Closed
Contributes to the affective attitude boredom. The muscular basis consists of relaxation of Levator palpebrae superioris.
Combinations of Action Units
AU 1 - 2 - 4
Contributes to the emotions fear and can be recognized by the wavy pattern of the wrinkles across the forehead.
AU 1 - 2
Contributes to the emotion surprise and can be recognized by a smooth line formed by the wrinkles across the forehead.
AU 1 - 4
Contributes to sadness. Recognizable by a wavy pattern of the wrinkles in the center of the forehead. Eye-brows come together and up.
AU 4 - 5
Contributes to the emotion anger.
AU 6 - 12
Contributes to happiness. Notice the wrinkles around the eyes caused by cheek raising, also known as the "Duchenne Marker".
AU 10 - 25
Contributes to the emotion disgust. When AU 10 is activated intensely, it causes the lips to part as the upper lip raises.
AU 18 - 23
Often confused as solely AU 18. Notice the lips almost appear to be pulled by a single string outward (AU 18) and then tightened (AU 23).
AU 23 - 24
The AUs marking lip movements are often the hardest to code. The lips are being pushed together (AU 24) and tightened (AU 23).