Development and Validation of the AIIMS Facial Toolbox for Emotion Recognition

Abstract

Background: Emotional facial expression database, used in emotion regulation studies, is a special set of pictures with high social and biological relevance. We present the AIIMS Facial Toolbox for Emotion Recognition (AFTER) database. It consists of pictures of 15 adult professional artists displaying seven facial expressions—neutral, happiness, anger, sadness, disgust, fear, and surprise. Methods: This cross-sectional study enrolled 15 volunteer students from a professional drama college in India (six males and nine females; mean age = 26.2 ± 1.93 years). They were instructed to pose with different emotional expressions in high and low intensity. A total of 240 pictures were captured in a brightly lit room against a common, light background. Each picture was validated independently by 19 mental health professionals and two professional teachers of dramatic art. Apart from recognition of emotional quality, ratings were done for each emotion on a 5-point Likert scale with respect to three dimensions—intensity, clarity, and genuineness. Results are discussed in terms of mean scores on all four parameters. Results: The percentage hit rate for all the emotions, after exclusion of contempt, was 84.3%, with the mean kappa for emotional expression being 0.68. Mean scores on intensity, clarity, and genuineness of the emotions depicted in the pictures were high. Conclusions: The database would be useful in the Indian context for researching facial emotion recognition. It has been validated among a group of experts and was found to have high inter-rater reliability.