Now You Can Read Horses’ Facial Expressions

Horse lovers everywhere can now read theirs horses’ facial expressions much easier thanks to researchers and the new methodology that easily categorizes 17 distinct facial expressions.

We Can Read Horses’ Facial Expressions Like We Do Humans

Researchers at the University of Sussex have published a new study that enables horse caretakers to systematically identify facial movements and correlate them to distinct facial expressions using a standardized method.

Though this is not the first research to analyze animals and their facial expressions, nor is it the first to study whether animals’ facial expressions are used to communicate emotions. However, it is the first published standard of measurement that can be used in detecting horses emotions through their facial expressions using a systematic approach.

Now You Can Read Horses' Facial Expressions - Clapway

The researchers believe that using this system will help caretakers understand and better take care of horses when they show signals of distress or other negative emotions.

Using Facial Recognition Software for Horses

The researchers took a novel approach to understanding horses facial expressions by using the Facial Action Coding Systems, or FACS, that was originally designed to study human facial expressions.

Simply put, FACS works by analyzing facial muscle anatomy and using an objective framework for categorizing emotions based on underlying muscle movements. Several expressions have been recorded and now are the basis for the FACS system of human facial expression in regards to human emotional expression.

The facial recognition software was pioneered through the codified FACS guidelines. Knowing that the FACS has been a helpful tool for psychologists, the animal researchers turned their attention to animal expression, choosing the horse for its first subject.

Horses were chosen for two very important reasons. First, they are visual and social animals that exhibit facial expressions. Second, the majestic animals have been domesticated for over thousands of years, allowing them to be studied easily as well as bringing them in more proximity with humans who need to understand their emotional states for a variety of reasons.

Using Facial Recognition for Horses to Create EquiFACS

The researchers were able to use FACS on horses by analyzing and comparing human facial anatomy to horse facial anatomy. Because they had to understand the intricacies of muscles and muscle attachments, they had to thoroughly investigate and understand the facial musculature movement to be able to code each movement to an emotional expression.

After 15 hours of video analysis taken from wild horses, researchers were able to identify not only facial expressions, but which muscles were used to make the expressions. The next step was to use the horse expressions to find the corresponding human expression.

Over 17 different facial expressions were observed that could correspond to humans, which allowed the researchers to organize their results into a code of behavioral sequences, a system they called EquiFACS.

Another interesting finding was that several of these expressions could also be found in other primates, dogs, and cats.

How EquiFACS Can Benefit Horses and Owners

Researchers tested EquiFACS using 4 experts, two in the field of FACS and two in the field of animal anatomy. All four experts agreed that the code was easy to use, which shows the potential for other people, such as owners, to also use the system to understand their animals.

Using EquiFACS may be beneficial for owners to better understand and care for their horses, but ultimately, it may be used to explore other animals and their facial expressions as well.

With this new tool, horses may have changed the way animal behavior and psychology is seen by promoting more respect, socialization and care for our domesticated friends through recognizing and understanding their facial expressions and emotions.

Credit for Title Picture: Flickr user peardg
Credit for Second Picture: Flickr user Pete Markham

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