# Review on BCI Virtual Rehabilitation and Remote Technology Based on EEG for Assistive Devices
## 3 Overview of BCI Technology and BCI-Based Rehabilitation  
Assistive technology is an object; piece of equipment; or commercial, homemade, or other product used to increase, maintain, or improve the functional capacities of individuals with some disability. These technologies can be as simple as glasses (to improve vision) or as complex as prosthetics, orthotics, and other devices dedicated to helping a person prevent loss of function or restore function. Among these technologies, BCI is a relevant technology due to its multiple applications in diverse rehabilitation methods. Figure 6[10] reflects the different impairments and some of the technologies available to restore functions and improve life quality.  
Figure 4: Number of publications related to “Virtual Rehabilitation and Assistive devices” by year [8].  
Figure 5: Literature map of citations of the present work.  
BCIs [11] are systems designed to study the brain's electrophysiological response and encode, which permits a person to communicate with the environment. Various biosignals can support BCI [12]. Those signals reflect the information of the body. They could be measured and monitored through EEG information, functional magnetic resonance imaging (fMRI), magnetic resonance imaging (MRI), electrocorticography (ECoG), magnetoencephalography (MEG), and others.  
For the implementation of BCI, EEG signals have gained great popularity among the different available biosignals due to their cost, real-time response, portability, and other factors mentioned in [13]. As EEG is a technique representing neurocognitive processes, this study captures the brain activity as a consequence of perception; talking, moving, and thinking are high-speed processes. Such a signal could be used in different BCI applications, as mentioned in [14], in various fields, such as gaming, arts, and health applications.  
BCIs could be helpful for rehabilitation. They may help patients visualize the restoration through computerized systems and reduce the possibility of abandoning therapy by showing the patient a gradual but objective improvement. As a result of the pandemic (COVID-19), rehabilitation services were severely affected or disrupted [15]. Hence, BCIs can help people access their therapies, a possible solution for removing the mobility barrier; with these techniques, patients will not need to be transferred to a medical center for rehabilitation.  
A human-computer interface is a connection between a person and a computer through technical devices, such as a suitable sensor. These systems have many design factors; one of the most important is the biosignal that triggers the system. Others are the algorithm that allows the classification of the signal, the way to control the system, and the final purpose or application of the rehabilitation system. For example, in [16] are highlighted not only the studies referred to as HCI or BCI that employ EEG signals, but those that use BCI triggered by electromyographic signals or a combination of both. Furthermore, some systems are triggered by other signals, such as EoG (electrooculography, the movement of the eye muscles).  
BCIs are systems that connect a computer and a human user based on the power of the brain signals (EEG). This interconnection is the reason that justifies this technology gaining popularity in the rehabilitation field [17]. Some advantages of choosing EEG as a trigger signal for BCI are mentioned in [13], such as the fact that EEG study can  
Figure 6: Specific impairments and related technologies.  
capture the brain activity dynamics because many cognitive processes (such as perception, linguistic, motor, and cognition itself) are high-speed processes. Additionally, this study measured the neurocognitive processes directly of the neural activity through the voltage fluctuations representing the neurons' biophysical changes. In contrast, there are a few disadvantages of analyzing EEG signals; most are related to the signal's complexity and consequent processing.