iMotions Facial Expression Data Skill

To process iMotions facial expression data for behavioral economics experiments, you can use this Skill to load CSV files, filter by experimental segments, and extract emotion metrics. It requires pandas for data manipulation and specific logic to map annotations to oTree periods.

Yes, you can analyze emotion metrics like Joy and Sadness during specific oTree trading periods. This Skill extracts key emotion metrics and aggregates them, enabling correlation with experimental events such as sell decisions within a MarketRuns session.

You filter iMotions facial expression data by using the Skill's phase filtering capabilities to precisely segment data by experimental segment, round, and phase. This allows targeted analysis of specific intervals like a MarketPeriod within a session.

Yes, this data processing Skill requires pandas to map iMotions annotations to oTree experimental periods. Pandas is a necessary dependency for manipulating the CSV data and executing the logic required to align facial expression metrics with experimental events.

The best way to correlate facial expression data with experimental sell decisions is to map iMotions annotations to oTree periods using this Skill. It facilitates the extraction of action unit data and emotion metrics, enabling direct correlation with behavioral events.

A limitation when extracting action unit data from iMotions CSV files is that the Skill relies on specific logic to map annotations to oTree periods. It is tailored for the MarketRuns experiment, so adapting it to other experimental frameworks may require custom adjustments.