# Integration Between Serious Games and EEG Signals:
## 3 Foundations of Serious Games in EEG-Based BCI Systems
### Brain-Computer Interfaces (BCI) and Electroencephalography (EEG) Signals  
The central nervous system (CNS) is composed of the brain and spinal cord; it is characterized primarily by its location within connective tissue membranes (meninges), by its distinctive cell types and histology, and by its function, which allows it to integrate a large number of sensory inputs to obtain effective motor outputs [36]. Now, the activity of the CNS includes electrophysiological, neurochemical, and metabolic phenomena (such as neuronal action potentials, synaptic potentials, neurotransmitter releases, and oxygen consumption). These phenomena occur continuously and can be monitored by measuring electric or magnetic fields, hemoglobin oxygenation, or other parameters using sensors on the surface of the brain or inside the brain [37]. Under the previous context, the term brain-computer interface (BCI) is introduced, which can be defined in different ways [38; 39; 40; 41]. In general, a BCI system measures brain activity and translates it into control signals, which are used in the construction of new technologies that allow for improving the quality of life of people (healthy or disabled) [42; 43; 44]. Devices that only monitor brain activity and do not use it to modify the ongoing interactions of the CNS with its environment are not considered BCI. The design of a BCI includes interdisciplinary knowledge, covering areas such as computer science, engineering, signal processing, neuroscience, and psychology. In general, two stages are required to use a BCI: (1) a training stage, in which (a) the user is trained to voluntarily control his or her brain potentials (in the case of the BCI operating condition), (b) an offline training stage, which calibrates the training algorithm (in the case of BCI pattern recognition), and (2) the online stage, in which the BCI system is used for control [45]. In online mode, the BCI system can be compared to a closed loop, which involves steps or tasks related to the control signals obtained from the brain: acquisition or measurement of brain activity, pre-processing, feature extraction, classification, translation into a command, and feedback [39; 45; 46]. Therefore, control signals obtained from the brain can be considered as the object of study in BCI systems. These signals can be presented in three categories: Evoked signals, spontaneous signals, and hybrid signals [47; 48; 49; 23; 40]. Furthermore, [PERSON] et al. [46] and [PERSON] et al. [40] consider that BCIs can be classified taking into account three aspects: reliability, invasiveness, and synchronization. With respect to reliability, BCIs can be dependent or independent, considering whether the experimental subject requires a certain level of motor control. Invasiveness refers to the way brain activity is measured or acquired (invasive, non-invasive, semi-invasive). Synchronization refers to the fact that the user's interaction with the system takes place within a certain period (synchronous) or the user is free to perform an activity or task at any time (asynchronous). In contrast, [PERSON] and [PERSON] divide BCI applications into two categories: medical applications and non-medical applications. The first category includes rehabilitation and control of prosthetic devices, medical diagnosis, assistive mobility, BCI-controlled web and music browsers, and mental status recognition, while non-medical BCI applications refer to video games, multimedia, or virtual reality [45]. Based on the previous arguments and considering the area of study of serious games, we limit this review work to dependent, noninvasive, and synchronous BCIs. Regarding the selection of electroencephalography (EEG), this is considered the most common method for recording brain signals; it is noninvasive, implemented in low-cost equipment, offers good communication and control channels, has high temporal resolution, and is safe, easy to use, and affordable [40,50].