# Review on BCI Virtual Rehabilitation and Remote Technology Based on EEG for Assistive Devices
## 9 BCI Applications for Rehabilitation
### BCI Devices for Rehabilitation
The features that could reflect the system's reliability are different depending on the energy and cost of the system, the ability of a bodied subject to perform a task, the need to avoid disruption of normal activities, cosmetics, and practicality. The challenges to the implementation of BCI rehabilitation are various, such as the data acquisition method, the signal processing and classification, the realization of a robot device, the need to proportionate an adequate feedback environment, and the integration of all the elements [79]. The existence of different devices explains the variety of implementations in the studies of BCI for rehabilitation. For example, reference [11] shows the studies related to BCIs for motor impairment, and some BCI modalities, such as slow cortical potentials, sensorimotor rhythms, and P300, used as the operational mechanisms for post-stroke and spinal cord injury rehabilitation. On the other hand, the review of [PERSON] [95] remarks on some ethical implications of the use of BCI technologies, as a part of some studies of BCI implementation from the medical perspective. The focus of the review of [PERSON] [96] was a methodical one, so the number of studies reviewed (eight) was small, but the study portrays the effectiveness of telehabilitation in the elderly population. Recently, in 2021, ref. [6] 39 studies were reviewed about BCI for rehabilitation. This study used statistical information about the paradigms that triggered the BCI mechanism and the diseases that the rehabilitation focused on. The most recent review about BCI rehabilitation was done by [PERSON] [97], and is an interesting one because it is the recompilation of 6 years of investigation to develop a project the name \"Feel Your Reach\". This project focuses on rehabilitating people with cervical SCI through the control of an assistive robotic arm for daily tasks using a non-invasive signal recording device. This review recapitulates many studies, such as the one of [PERSON] et al., who in 2018 [59] did research that used both EEG and EMG signals to reflect motion and fatigue patterns and bring feedback to the virtual system. They adapted a training scene based on the fatigue status. They used a Visual Studio developer to create the rehabilitation scene that consisted of \"flying a plane\", \"pushing a box\", and \"Tetris\". The data passed through  
Figure 11: Sample of myoelectric commercial devices. an SVM classifier to control the virtual environment. The effectiveness of the action for healthy people was reported to be 99.5%, and it was 94.75% for patients. A few later, [PERSON] et al. [98] applied a rehabilitation measure after a stroke by integrating an EEG BCI with VRy. A 60-year-old patient was teated for three weeks in a clinical setting. They measured the upper extremity scores using the full Meyer scale (FMA UE) and the brain plasticity. The team used a NeuroRow BCI-VRy System. The data acquisition used an Enobio 8, an 8-channel sensor. The virtual environment designed was a bat rowing atmosphere. The results reflected an FMA scale of 31 pre-rehabilitation, 40 post-rehabilitation, and 44 after one month (the follow-up score). Then, they used an LDA classifier to measure the performance through 10 sessions. The patient had 60% accuracy in the task versus the healthy group and used VRy with 76% accuracy; the non-VRy group reported 68% accuracy. [PERSON] and [PERSON] [74] proposed a virtual rehabilitation training system based on EMG and EEG. This system collects signals synchronously and obtains ERD/ERS (event-related desynchronization and synchronization). These coefficients use an SVM-PSO method to select the best combination of EEG-EMG to avoid fatigue using MSC. Adams software that has the purpose of virtual prototyping. This makes the proposed exercise recognize a motion pattern. In the present year, [PERSON] [99] created a virtual ambiance controlled by an assistance robot designed to help with household tasks.