There exist a few examples of hybrid BCIs. Some are based on multiple brain signals. One of such hBCIs is the combination of motor imagery (MI)-based BCI with ErrP detection and correction of false mental commands (Ferrez and Millán, 2008b). A second example is the combination of MI with steady state visual evoked potentials (SSVEPs) explored in some offline studies (Allison et al., 2010; Brunner et al., 2010). Other hBCIs combine brain and other biosignals. For instance, Scherer et al. (2007b) combined a standard SSVEP BCI with an on/off switch controlled by heart rate variation. Here the focus is to give users the ability to use the BCI only when they want or need to use it. Alternatively, and following the idea of enhancing people's residual capabilities with a BCI, Leeb et al. (2010b) fused EMG with EEG activity, so that the subjects could achieve a good control of their hBCI independently of their level of muscular fatigue. Finally, EEG signals could be combined with eye gaze (Danoczy et al., 2008). Pfurtscheller et al. (2010) have recently reviewed preliminary attempts, and feasibility studies, to develop hBCIs combining multiple brain signals alone or with other biosignals. Finally, hybrid BCIs could exploit several brain imaging techniques simultaneously; i.e., EEG together with MEG, fMRI, NIRS, and even TMS. As mentioned above, our focus in this review paper is on principles to develop hBCI that, when coupled with existing AT used by disabled people, can effectively improve their quality of life.