Evaluation Summary
This paper describes the development and validation of an automatic approach that leverages machine vision and learning techniques to quantify dynamic facial expressions of emotion. The potential clinical and translational significance of this automated approach is then examined in a "proof-of-concept" follow-on study, which leveraged video recordings of depressed individuals watching humorous and sad video clips.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their name with the authors.)