Human faces express emotions, informing others about their affective states. In order to measure expressions of emotion, facial Electromyography (EMG) has widely been used, requiring electrodes and technical equipment. More recently, emotion recognition software has been developed that detects emotions from video recordings of human faces. However, its validity and comparability to EMG measures is unclear. The aim of the current study was to compare the Affectiva Affdex emotion recognition software by iMotions with EMG measurements of the zygomaticus mayor and corrugator supercilii muscle, concerning its ability to identify happy, angry and neutral faces. Twenty participants imitated these facial expressions while videos and EMG were recorded. Happy and angry expressions were detected by both the software and by EMG above chance, while neutral expressions were more often falsely identified as negative by EMG compared to the software. Overall, EMG and software values correlated highly. In conclusion, Affectiva Affdex software can identify facial expressions and its results are comparable to EMG findings.
Related Posts
-
Combatting Fraud in Online Surveys: What To Do When Your Respondents Aren’t Real
-
Human-in-the-Loop Digital Twins: How Real-Time Biosensor Data Is Transforming Simulator Research
-
Digital Twins in Consumer Research: Validating Synthetic Behavior with Biosensors
-
Forensic Science: Leveraging Human Behavior Research to Go Beyond the Crime Scene
