You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A review of hybrid brain-computer interface systems 
Chapter Title:  Advances in Human-Computer Interaction 5 
1. Abstract of Cited Paper (BIB001):  We propose an on-line hybrid BCI system that combines P300 and ERD. By employing both brain activity patterns (BAPs) in parallel and asynchronously, the system can issue different types of commands, for example, in robotic control scenarios. We present a method for reliably distinguishing between the two BAPs. We examined the level of false positives in P300 classification while a subject tries to evoke an ERD. We found this level to be as low as for regular P300 trials. Our system thus assumes the presence of ERD whenever classification of all P300 symbols is negative. Empirical results indicate that subjects can achieve good control over the hybrid BCI. In particular, subjects can switch spontaneously and reliably between the two BAPs.

Literature Review:
Step 2 (Navigation). An autonomous motion control was introduced for this step. The destination was selected and the wheelchair started its motion toward the destination following virtual guiding paths. A proximity sensor was considered for stopping the wheelchair facing obstacles. Step 3 (Stopping Command). For this control command, the interface needs to be fast, reliable and have a low false acceptance rate. Two approaches for a stopping command were presented. The first approach was the fast P300, in which, on the screen, there is only one item "The Stop" and the task is the detection of user's intention. Experimental results showed reduction in response time. However, increase in false acceptance makes this approach inapplicable. The second approach was to use a mu-beta BCI. The position of a cursor was considered for presenting the visual feedback for the mu-beta BCI system and the control of the cursor was based on an arm movement imagination. Results showed approximately the same response time as the fast P300 approach, but for false acceptance, a rate of zero was achieved. Since the low false acceptance rate and fast response are the most important needs for this type of BCI, it seems that mubeta BCI is a more reliable system for this application. In BIB001 , different states and control commands needed for operating the system were controlled in a virtual environment. P300/MI hybrid BCI was used for operating the system. Two sequential states covered the areas of the virtual environment, navigation, and device control state. The interface strategy is explained as follows. For navigation, MI BCI was used with the continuous control commands limited number of commands. By imagination of left and right hand movement, control commands were issued. The position in the virtual environment was updated by each control command. In the device control state, the commands were discrete. By considering features of control commands and paradigms, an interface was developed. For this paradigm, the P300 oddball paradigm was considered. When the area coverage changed to the device control state, the MI command detection stopped and the controller switched to system state. The system state then switched to device control state automatically. The P300 BCI presented the control panel to subjects. A switch for navigation happened by the selection of the "quit" command using the P300 oddball paradigm. If the "quit" was not detected after 6 commands, the controller would switch to the system state automatically. Experiments were performed by four subjects. To evaluate the hybrid approach, the experiment was also implemented for P300 and MI BCIs separately. 22 testing runs were considered in three blocks: (1) A block for hybrid control testing, (2) A block for MI-based navigation, and (3) A block for P300-based device control. Three tasks with a combination of navigation and device control commands were considered for evaluating the hybrid control strategy. In block presenting MI-based navigation, the tasks were the same, with the difference that in the device control state areas, the device control panels were not evoked. In the third block, navigation was not available and two of the tasks were tested for P300 BCI evaluation. The online accuracy was used for comparing different approaches. Comparing the P300 task in the hybrid BCI and the single P300 BCI showed little reduction in the accuracy of the hybrid strategy. The accuracy for two of the subjects reduced in MI part of the hybrid BCI compared to the single MI BCI. However, by utilizing the hybrid BCI, more complicated tasks can be accomplished in a virtual environment. In BIB002 , P300 and ERD were introduced to be components of the hybrid BCI in robotic control decision applications. Parallel and asynchronous classifications were introduced. The system task was to detect the intended pattern. Classification accuracy was evaluated during the experiment, which was considered for presenting the hybrid. Sixty trials were presented to four subjects: thirty trials for P300 presentation and thirty trials for MI. During the second thirty trials, the P300 stimuli were also presented but the subjects were not supposed to pay any attention to the stimuli.