# Emotional Health Detection in HAR: New Approach Using Ensemble SNN
## 3 Emotion Recognition Analysis
### Dataset Used  
The public databases used for analyzing emotions are the BU-3 DFE and the BU-4 DFE.  
The BU-3 DFE [42] is a 3D facial model database at Binghamton University containing facial images of 100 subjects of different ethnic and racial origins. Each subject was scanned with seven expressions. Except for the neutral expression, each of the six basic expressions (happiness, disgust, fear, anger, surprise, and sadness) includes four intensity levels. Thus, there are a total of 2500 3D facial expression models. Each expression pattern has an image of the corresponding facial texture captured at two views (approximately \(+45^{\circ}\) and \(-45^{\circ}\)). As a result, the database consists of 2500 two-view texture images and 2500 geometric shape models. To analyze facial behavior from static 3D to dynamic 3D space, the BU-3 DFE was extended to the BU-4 DFE [42]. The new database of high-resolution 3D dynamic facial expressions refers to 101 subjects of different sexes, ages, racial and ethnic origins. Three-dimensional facial expressions were captured at a rate of 25 frames per second. Each sequence of expressions contains approximately 100 frames. Eachsubject performed the six basic emotions, ending with the neutral expression. The database contains 606 sequences of 3D facial expressions.  
Another database used is the Bosphorus [43], which contains 2D and 3D images of 105 subjects, of which a third are professional actors and actresses. The data were collected in the laboratory, and the subjects were instructed to perform the seven basic facial expressions. The scans for the 105 subjects were carried out considering different poses, expressions, and occlusion conditions. The total number of facial scans is 4666. This database contains examples of the unit of action (A.U.) faces defined in the facial action coding system.  
Other databases with visual sequences and images are available for studying emotions; some examples are presented below.  
The extended Cohn-Kanade Dataset (cK+) [44] contains 593 sequences of 123 subjects. The sequence of images varies in duration from 10 to 60 frames. The images are labeled with seven emotions, including six basic emotions and contempt. All images were taken with a constant background. To avoid mistakes during the training phase, the labels were assigned respecting the coding of FACS emotions.  
Another database is the CASME [45], which contains spontaneous microexpressions. Microexpressions are fleeting facial expressions that reveal authentic emotions that people try to hide. From the 1500 facial movements filmed at 60 fps, 195 microexpressions were selected. Samples from the dataset were taken from thirty-five participants. Each clip has a minimum length of 500 ms. The images were labeled based on psychological studies and participants' self-assessments.  
Still, the FER-2013 [46] is a widely used dataset containing 28,000 training data, 3500 validation data, and 3500 test data. Land images are stored in a spreadsheet where the pixel values of each image are reported in cells per row. The images were obtained using Google search and then grouped by emotional classes. The images were collected from varying poses, ages, and occlusion.  
BAUM [47] is a spontaneous audiovisual facial database of affective and mental states. Video clips were obtained by shooting subjects from a front view using a stereo camera and a semi-profile view using a mono camera. Subjects were shown images and short video clips to evoke emotions and mental states. The target emotions are happiness, anger, sadness, disgust, fear, surprise, boredom, and contempt; mental targets are uncertain (even confused, indecisive), thoughtful, focused, interested (even curious), and annoyed. The database contains 273 clips obtained from 31 subjects (13 females, 18 males) with the age range of subjects being 19-65 years.