## 4 Results and Discussion
### Classification of Articles by Application Domain and Field
#### 4.2.2 Non-Medical Applications  
EEGs have been utilized in numerous non-medical applications. These applications are employed for both healthy and physically challenged individuals. Non-medical fields where EEGs have been applied include entertainment, education, monitoring, and gaming. Table 7 shows a classification of non-medical articles into areas of application: Monitoring (95 articles, 43.6%), New method (60 articles, 27.5%), Entertainment (25 articles, 11.5%), Marketing (4 articles, 1.8%), Education (2 articles, 0.9%), Assistance (10 articles, 4.6%), and Other (22 articles, 6.4%). \begin{table}
\begin{tabular}{p{14.2 pt} p{142.3 pt} p{142.3 pt}} \hline \hline
**Domain** & **Description** & **References** \\ \hline \multirow{8}{*}{Monitoring} & These articles explored the effects of different types of stimuli, test emotions, and elicitation methods. They also investigated how different types of stimuli induce specific emotional reactions. They identified efforts in brain and lateralization, which aims to define regions of the brain and the functioning of specific behaviors and cognitive skills. They also compared emotional responses between genders and during human developmental stages. & [26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 64; 65; 67; 70; 74; 77; 78; 80; 82; 87; 89; 91; 93; 96; 97; 91; 113; 127; 128; 132; 134; 138; 139; 141; 144; 147; 148; 150; 155; 158; 159; 161; 163; 164; 166; 169; 164; 165; 169; 172; 175; 177; 179; 182; 184; 187; 192,120; 215,241; 261] \\ \hline \multirow{8}{*}{New method} & These articles proposed approaches for detecting affective states using single/multi-modality signal processing methods, including feature extraction and selection, machine learning and pattern recognition methods. These proposed systems aim to explore or improve EEG-based emotion recognition systems. & [2, 39; 41; 42; 49; 50; 57; 61; 63; 92; 104; 108; 109; 117; 131; 136; 149; 152; 157; 173; 174; 185; 186; 189; 191; 195; 209; 217; 219; 223; 225; 229; 262; 227; 228; 229; 221; 223; 225; 229; 263; 227; 229; 223; 234; 235; 236; 237; 238; 239; 240; 241; 242; 243; 244; 245; 246; 247; 248; 249; 250; 251; 252; 253; 254; 255; 256; 25 Different approaches have been proposed, and several research groups have developed EEG-based BCI systems that aim to detect affective state. Examples of non-medical applications are hereafter identified. Recently, a new research area appeared in the marketing field: neuro-marketing. The goal of this new area is to understand consumer responses toward marketing stimuli by using imaging techniques and the recognition of physiological parameters. Because customer feelings in sales areas are strongly influenced by the perception of the surroundings, recognition of emotional responses can reveal true consumer preferences and improve and assist in the (buying) process. Four articles have presented this idea in different applications [102; 123; 218; 280]. Similarly, an EEG-based experimental study [144] is also used to identify the temporal point at which smokers' responses to health warnings begin to differ. Basically, they aim to determine the effects of graphic pictorial cigarette package health warnings by assessing the selective attentional orientation and measuring emotional processing; they reported that smokers are less sensitive to the emotional content of cigarette health warnings. Therefore, future health warning development should focus on increasing the emotional salience of the pictorial health warning content among smokers. Three research groups have explored EEG emotion detection systems for emotion (stress) monitoring during self-driving of a powered wheelchair [40; 227; 285]. These studies aim to investigate the ability to assist and enhance BCI-based wheelchairs by integrating emotion detection while controlling a wheelchair. The relationship between music genres and human emotions has been investigated in several recent BCI studies.