Paul Ekman, perhaps the world’s most famous face reader, pioneered the study of facial expressions in the 1970s, creating a catalog of more than 5,000 muscle movements to show how the subtlest wrinkling of the nose or lift of an eyebrow reveal hidden emotions.

Now, a group of young companies with names like Emotient Inc., Affectiva Inc. and Eyeris are using Dr. Ekman’s research as the backbone of a technology that relies on algorithms to analyze people’s faces and potentially discover their deepest feelings. Collectively, they are amassing an enormous visual database of human emotions, seeking patterns that can predict emotional reactions and behavior on a massive scale.

So far, the technology has been used mostly for market research. Emotient, a San Diego startup whose software can recognize emotions from a database of microexpressions that happen in a fraction of a second, has worked with Honda Motor Co. and Procter & Gamble Co. to gauge people’s emotions as they try out products. Affectiva, an emotion-detection software maker based in Waltham, Mass., has used webcams to monitor consumers as they watch ads for companies like Coca-Cola Co. and Unilever PLC.

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