# Towards Detection of Interest Using Physiological Sensors
## 3 Physiological Patterns and Features of Interest
### EEG and ECG Patterns  
As shown in Table 1 below, the EEG channels and devices used vary from one study to another. This diversity in equipment specifications could be related to the differences in the purpose of the study, brain areas of interest, availability of devices, cost of devices, and required features. We are interested in patterns of brain activity leading to high detection and/or prediction rates for the state of interest. EEG may be the widely most studied tool in computational studies of emotional systems [51]. This is because new EEG products are more flexible and portable, relatively low cost, and produce high-quality data using fewer channels. In addition, some EEG devices are using dry sensors. EEG devices record brain activity in the form of electrical signals measured in microvolts and/or millivolts. These signals are produced by the brain and are recorded by placing specific electrodes on the scalp. Compared to functional magnetic resonance imaging, EEG produces data with a better temporal resolution, as it can acquire signals in milliseconds. Raw EEG data must undergo pre-processing, which includes, but is not limited to cleaning, that includes noise removal and filtering techniques, in order to be suitable for processing and analysis. Table 1 also lists other sensors that are normally used along with EEG, including ECG, GSR sensors, HR sensors, and electrooculography (EOG), which are known to produce data indicative of the emotional state of the subject. ECG devices record changes in electrical activity across the heart. ECG recordings are performed with each heartbeat over time in a process similar to HR sensor. Increases in HR may reflect cognitive processing, while decreased HR is indicative of attention to environmental stimuli [52]. GSR sensors are attached to the fingers of the subject's non-dominant hand. Correlations between HR and GSR parameters and valence and arousal are highlighted in several studies, e.g., [53]. EOG is sensitive and is used for correcting and cleaning eye blinking artifacts. All the EEG studies described below utilized questionnaires to confirm, classify, or support the findings based on data from the physiological sensors. We will not discuss this aspect of the studies, as this paper aims to examine physiological parameters. For further review of the subjective measures of interest, the reader is advised to see [54; 55]. We, therefore, only mention the use of questionnaires when necessary. Another topic of interest is the baseline session or the resting-state period. These sessions are used to obtain data from the subject in neutral or stimulus-free conditions. The duration of the baseline recording varies from one experiment to another and often ranges between 1 and 5 min in EEG studies. Because the physiological state of an individual is subjective and varies regularly, recording the baseline state is essential when comparing the subject's state in the presence or absence of a stimulation. Differences between these two conditions (baseline and stimulation) are later used for further analyses and calculations. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Study** & **Purpose** & **Participants** & **Emotion** & **Technology** & **EEG Channels** & **Stimuli** & **Measurement** & **Feature Selection** & **Classifier** & **Remarks** \\ \hline \hline
**Stimuli** & \begin{tabular}{c} Ensuming \\ \(\pm\) 1, \\ \end{tabular}  & \begin{tabular}{c} Ensuming \\ whether level of \\ \(\pm\) 2005 \\ \end{tabular}  & \begin{tabular}{c} Ensuming \\ whether level of \\ \(\pm\) 2005 \\ \end{tabular}  & \begin{tabular}{c} Ensuming \\ whether level of \\ \(\pm\) 2005 \\ \end{tabular}  & \ \begin{tabular}{c} Ensuming \\ \(\pm\) 1000 \\ \end{tabular}  &
\begin{tabular}{c} FPI, PIP, PI,  
[PERSON] et al. [8] have referred to interest as an approach-withdrawal (AW) index. They computed this index by assessing the difference between the average power of the alpha band recorded from left and right EEG frontal lobes channels.