Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> Abstract An internally or externally paced event results not only in the generation of an event-related potential (ERP) but also in a change in the ongoing EEG/MEG in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). The ERP on the one side and the ERD/ERS on the other side are different responses of neuronal structures in the brain. While the former is phase-locked, the latter is not phase-locked to the event. The most important difference between both phenomena is that the ERD/ERS is highly frequency band-specific, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously. Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments. <s> BIB001 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> A "virtual keyboard" (VK) is a letter spelling device operated for example by spontaneous electroencephalogram (EEG), whereby the EEC is modulated by mental hand and leg motor imagery. We report on three able-bodied subjects, operating the VK. The ability in the use of the VK varies between 0.85 and 0.5 letters/min in error-free writing. <s> BIB002 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> Abstract This case study demonstrates the coupling of an electroencephalogram (EEG)-based Brain–Computer Interface (BCI) with an implanted neuroprosthesis (Freehand ® system). Because the patient was available for only 3 days, the goal was to demonstrate the possibility of a patient gaining control over the motor imagery-based Graz BCI system within a very short training period. By applying himself to an organized and coordinated training procedure, the patient was able to generate distinctive EEG-patterns by the imagination of movements of his paralyzed left hand. These patterns consisted of power decreases in specific frequency bands that could be classified by the BCI. The output signal of the BCI emulated the shoulder joystick usually used, and by consecutive imaginations the patient was able to switch between different grasp phases of the lateral grasp that the Freehand ® system provided. By performing a part of the grasp-release test, the patient was able to move a simple object from one place to another. The results presented in this work give evidence that Brain–Computer Interfaces are an option for the control of neuroprostheses in patients with high spinal cord lesions. The fact that the user learned to control the BCI in a comparatively short time indicates that this method may also be an alternative approach for clinical purposes. <s> BIB003 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> We present a study of linear, quadratic and regularized discriminant analysis (RDA) applied to motor imagery data of three subjects. The aim of the work was to find out which classifier can separate better these two-class motor imagery data: linear, quadratic or some function in between the linear and quadratic solutions. Discriminant analysis methods were tested with two different feature extraction techniques, adaptive autoregressive parameters and logarithmic band power estimates, which are commonly used in brain–computer interface research. Differences in classification accuracy of the classifiers were found when using different amounts of data; if a small amount was available, the best classifier was linear discriminant analysis (LDA) and if enough data were available all three classifiers performed very similar. This suggests that the effort needed to find regularizing parameters for RDA can be avoided by using LDA. <s> BIB004 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> We have previously demonstrated that an EEG-controlled web browser based on self-regulation of slow cortical potentials (SCPs) enables severely paralyzed patients to browse the internet independently of any voluntary muscle control. However, this system had several shortcomings, among them that patients could only browse within a limited number of web pages and had to select links from an alphabetical list, causing problems if the link names were identical or if they were unknown to the user (as in graphical links). Here we describe a new EEG-controlled web browser, called Nessi, which overcomes these shortcomings. In Nessi, the open source browser, Mozilla, was extended by graphical in-place markers, whereby different brain responses correspond to different frame colors placed around selectable items, enabling the user to select any link on a web page. Besides links, other interactive elements are accessible to the user, such as e-mail and virtual keyboards, opening up a wide range of hypertext-based applications. <s> BIB005 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> Brain–computer interfaces (BCIs) can provide non-muscular communication and control for people with severe motor disabilities. Current BCIs use a variety of invasive and non-invasive methods to record brain signals and a variety of signal processing methods. Whatever the recording and processing methods used, BCI performance (e.g. the ability of a BCI to control movement of a computer cursor) is highly variable and, by the standards applied to neuromuscular control, could be described as ataxic. In an effort to understand this imperfection, this paper discusses the relevance of two principles that underlie the brain's normal motor outputs. The first principle is that motor outputs are normally produced by the combined activity of many CNS areas, from the cortex to the spinal cord. Together, these areas produce appropriate control of the spinal motoneurons that activate muscles. The second principle is that the acquisition and life-long preservation of motor skills depends on continual adaptive plasticity throughout the CNS. This plasticity optimizes the control of spinal motoneurons. In the light of these two principles, a BCI may be viewed as a system that changes the outcome of CNS activity from control of spinal motoneurons to, instead, control of the cortical (or other) area whose signals are used by the BCI to determine the user's intent. In essence, a BCI attempts to assign to cortical neurons the role normally performed by spinal motoneurons. Thus, a BCI requires that the many CNS areas involved in producing normal motor actions change their roles so as to optimize the control of cortical neurons rather than spinal motoneurons. The disconcerting variability of BCI performance may stem in large part from the challenge presented by the need for this unnatural adaptation. This difficulty might be reduced, and BCI development might thereby benefit, by adopting a ‘goal-selection’ rather than a ‘process- control’ strategy. In ‘process control’, a BCI manages all the intricate high-speed interactions involved in movement. In ‘goal selection’, by contrast, the BCI simply communicates the user's goal to software that handles the high–speed interactions needed to achieve the goal. Not only is ‘goal selection’ less demanding, but also, by delegating lower-level aspects of motor control to another structure (rather than requiring that the cortex do everything), it more closely resembles the distributed operation characteristic of normal motor control. <s> BIB006 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Asynchronous BCI <s> A motor imagery based brain?computer interface (BCI) provides a non-muscular communication channel that enables people with paralysis to control external devices using their motor imagination. Reducing the number of electrodes is critical to improving the portability and practicability of the BCI system. A novel method is proposed to reduce the number of electrodes to a total of four by finding the optimal positions of two bipolar electrodes. Independent component analysis (ICA) is applied to find the source components of mu and alpha rhythms, and optimal electrodes are chosen by comparing the projection weights of sources on each channel. The results of eight subjects demonstrate the better classification performance of the optimal layout compared with traditional layouts, and the stability of this optimal layout over a one week interval was further verified. <s> BIB007
Some asynchronous BCI use slow cortical potentials (SCP) corresponding to shifts of the mean potential measured on the cortex. Relatively long recording times (several seconds) are required before being able to discriminate between a positive and a negative shift of these potentials. A negative shift of the cortical potentials is associated to a significant cortical activity (imagination of movements or mental tasks) while a positive shift corresponds to a reduced activity. The main advantage of the use of SCP is the relative simplicity of the processing of these EEG signals, requiring only filtering and artefacts corrections. The major disadvantage is related to the need for more or less long training before the user is able to control the interface with an acceptable accuracy. The most well known application using SCP is the TTD developed at the University of Tübingen in Germany  . From this TTD, an internet navigator called NESSI was developed BIB005 . Another kind of asynchronous interface can be obtained from the processing of sensorimotor rhythms Mu and Beta associated to the imagination of the movements of the right and left arms or hand for example. The interfaces built from sensorimotor rhythms use mainly cursor displacement on the screen controlled by the magnitude of Mu and Beta waves associated to the cerebral activity in the sensorimotor cortex. The Mu waves frequency range is between 8 and 12 Hz and the Beta waves frequency range is between 18 to 26 Hz. These waves present interesting properties for BCI because they are associated to region of the cortex directly connected to the control of motor activity. Any preparation of a movement accomplished or imagined by the right arm or hand, respectively left, result in a decrease of the amplitude of these Mu and Beta waves detected on the left hemisphere, respectively right, of the sensorimotor cortex. This decrease of amplitude of the Mu and Beta rhythms is due to the desynchronisation of neuronal activity in the sensorimotor cortex of the hemisphere opposed to the requested arm or hand, this phenomenon is called ERD for Event Related Desynchronisation BIB001 . The change in amplitude or energy contained in the Mu and Beta bands is the feature that must be extracted from EEG signals. This one can thus be quite simply obtained by estimating the energy of the signals obtained by two band pass filters, one covering the Mu band and the other the Beta band BIB001 . Another procedure consists in making an autoregressive frequential analysis in an adaptive way in order to extract relevant parameters continuously with a greater speed  . After this step of feature extraction, classification is generally necessary to discriminate between the two classes (right-hand side or left) starting from the parameters which it was possible to extract from the signals. Studies showed the good robustness of the linear discriminating analysis in this type of study BIB004 . A continuous value is obtained from classification, and from this value, it is possible to control the interface in real time. The interface is thus controlled in a continuous way, allowing applications like the displacement of a cursor or an object on a screen. Several alternative communication interfaces use this approach to carry out the selection of item by controlling the displacement of a cursor towards the target corresponding to the choice of the subject  BIB002 . A continuous control is even much more important in applications where the subject must control prosthesis or the displacement of his wheelchair BIB003  . These applications require, in addition to continuous control, a good accuracy which is generally the case for BCI based on sensorimotor activity. Another advantage of the use of the Mu and Beta rhythms comes from the relatively good localization of them on the cortex, which makes it possible to consider applications based on only 2 EEG sensors BIB007 . However the major disadvantage of asynchronous BCI like those based on the sensorimotor activity is the need for relatively long training sessions before being able to control the interface accurately. Insofar as these brain computer interfaces short-circuit the defective transmission of information between the brain and the muscles, it is possible to imagine building interfaces ensuring a faster transmission and thus acceleration in the execution of orders of the brain. However, in practice, it is for the moment difficult to obtain higher performances in term of speed and reliability of transmission starting from brain computer interfaces. Experiments comparing times of positioning one cursor on the screen of a computer starting from a joystick and starting from the EEG signals coming from the sensorimotor cortex show the advantage in term of speed and accuracy of the use of the joystick  . Results of works on brain computer interfaces based on sensorimotor EEG signals show the very strong variability of the performances as one of the main difficulty to overcome BIB006 . Indeed whatever the measures (EEG or ECoG), the methods of analysis of the signals, the studied subjects, it always remains a significant problem of performances reproducibility. The origin of this problem is still difficult to define, for some researchers it is not due to the methods of measurements and analysis, in spite of the progress obtained following many works during the 20 last years, but more surely due to the higher difficulty for someone to control his EEG signals coming from the sensorimotor cortex than to control his muscles BIB006 . Relatively long training sessions are necessary to control EEG signals, this training being done by a visual feedback of the tasks carried out on the screen of the computer. Nevertheless it remains difficult, including for the most gifted subjects, to reproduce with the same reliability and the same speed of the actions carried out by our muscles starting from the control of our cerebral activity in the sensorimotor cortex.