## 4 Results and Discussion
### Classification of Articles by Application Domain and Field
#### 4.2.1 Medical Applications
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Domain** & **Description** & **References** \\ \hline Assessment & These articles assess the performance in terms of health and non-health. The data from these articles can be used in evaluating severity level and monitoring progress and attainment. Moreover, information from these studies is used to develop a scoring system to assess emotionality. & [4; 47; 72; 79; 94; 106; 118; 120; 133; 135; 145; 153; 167; 212; 213; 230; 231; 232; 233; 234; 235] \\ \hline Assistance & These articles provide insight into technologies/resources for a patient with a disorder/learning problem by means of assistive tools. Assistance occurs after the emotion detection methods have been used to identify skills and limitations of potential users. & [6; 33; 90; 103; 125; 140; 146; 165; 168; 180; 221; 236; 237] \\ \hline Diagnosis & These articles describe how doctors use EEG in the interpretation of medical conditions. EEG is used by clinicians as a diagnostic tool for patients with psychiatric and neurological disorders. EEG studies produce conclusive results as per the symptoms experienced by the patients. Most of these symptoms are emotional; hence, they are difficult to diagnose using subjective means. The goal of these systems is to objectively detect medical anomalies in a patient’s emotional affective state. & [5; 52; 54; 73; 75; 81; 98; 99; 107; 114; 121; 122; 124; 126; 156; 181; 221; 238; 239; 240] \\ \hline Monitoring & These are review studies that report previous research efforts. They serve as avenues for increasing the awareness of EEG emotional response studies. They also increase the awareness of how EEG may be used in clinical practice to uncover potential neurophysiologic abnormalities. & [17; 18; 19; 21] \\ \hline Other &
\begin{tabular}{p{56.9 pt} p{113.8 pt}} \hline \hline \end{tabular}
\end{table} 
Table 6: Medical application classification. Persons with Parkinson's disease have shown deficits in emotional recognition abilities. Research findings on the reason for this are inconclusive. Nine articles discussed the idea of using EEG-based emotion detection to provide assistance, monitoring, assessment, and diagnosis of [PERSON]'s disease in patients [47; 106; 114; 118; 119; 120; 121; 122]. EEG-based emotion detection systems for cochlear implant patients have been proposed in [156; 211; 238]. EEG signals are used to estimate the ability of these patients to recognize emotional sounds by using EEG signals and different stimuli. Three studies compared the emotional approaches of two groups of study participants. In one group, which was comprised of children with normal hearing, the participants displayed a withdrawal/approach model, whereas the cochlear implant users did not. Other medical cases include autism [6; 211; 75; 140; 212; 213], bipolar disorder [124; 145], epilepsy [230; 234; 235], attention-deficit/hyperactivity disorder [103; 165], bulimia nervosa [33; 168], borderline personality disorder [167], pervasive developmental disorder [81], and eye movement desensitization and reprocessing [125].