Several add-on modules expand FaceReader software to meet your research needs. For example, if you are looking for an easy way to analyze and report your results in detail, the Project Analysis Module will help you with that. Moreover, the Action Unit Module offers you automatic analysis of 20 Action Units. The third module we provide enables you to estimate the heart rates of the test participants.
Project Analysis Module
For advanced analysis of facial expression data, the Project Analysis Module should be part of your software. You can easily evaluate stimuli, such as a commercial or an image, by comparing male participants to female participants, for example.
The Project Analysis Module includes the Stimulus Presentation Tool. By designing a test, this tool automatically shows the test participants the stimuli while FaceReader accurately analyzes the participant’s face.
Action Unit Module
Action Unit classification adds valuable information to facial expressions recorded by FaceReader. This add-on module allows for the automatic analysis of a selection of 20 common Action Units, such as raising of cheeks, wrinkling of nose, dimpling, and lip tightening.
To measure affective attitudes, such as interest, boredom, and confusion, a trigger condition, including activation or non-activation of specific Action Units, is met. The emotional state confusion is, for example, correlated with either Action Unit 4 (Brow Lowerer) or 7 (Eyelid tightener).
Remote Photoplethysmography (RPPG)
With this module, based on patented technology, you can analyze heart rate of the test participant without additional hardware, using the FaceReader camera. The Photoplethysmography (PPG) technique measures the small changes in color caused by changes in blood volume under the skin epidermis. Determining the subject’s heart rate can be particularly useful as an additional indicator of arousal for subjects or situations where there is little variation in facial expressions.
Now available: a prototype of Baby FaceReader! Baby FaceReader is under development, and can automatically measure facial expressions in infants ranging in age from 6 to 24 months old.
Because infants are unable to provide verbal feedback, their facial expressions are particularly insightful, for example to identify their responses to taste and other sensory stimuli, to examine parent-child interaction, or to research changes and stabilities in infants' facial expressions.
FaceReader methodology note
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