Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> Abstract This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., ‘locked-in’ patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min. <s> BIB001 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> The purpose of this study was to develop a real-time electromyogram (EMG) discrimination system to provide control commands for man-machine interface applications. A host computer with a plug-in data acquisition and processing board containing a TMS320 C31 floating-point digital signal processor was used to attain real-time EMG classification. Two-channel EMG signals were collected by two pairs of surface electrodes located bilaterally between the sternocleidomastoid and the upper trapezius. Five motions of the neck and shoulders were discriminated for each subject. The zero-crossing rate was employed to detect the onset of muscle contraction. The cepstral coefficients, derived from autoregressive coefficients and estimated by a recursive least square algorithm, were used as the recognition features. These features were then discriminated using a modified maximum likelihood distance classifier. The total response time of this EMG discrimination system was achieved about within 0.17 s. Four able bodied and two C5/6 quadriplegic subjects took part in the experiment, and achieved 95% mean recognition rate in discrimination between the five specific motions. The response time and the reliability of recognition indicate that this system has the potential to discriminate body motions for man-machine interface applications. <s> BIB002 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> The purpose of this study is to develop a human-computer interface (HCI) application based on a real-time EMG discrimination system. A personal computer with a plug-in data acquisition and processing board containing a floating-point digital signal processor are used to attain real-time EMG classification. The integrated EMG is employed to detect the onset of muscle contraction. The cepstral coefficients derived from AR coefficients and estimated by a recursive least square algorithm, are used as the recognition feature. These features are then discriminated using a modified maximum likelihood distance classifier. The identified commands control the mouse cursor. It is fully compatible with a Microsoft serial mouse. This system can move the cursor in four directions, and double-click the icon in GUI operating systems. <s> BIB003 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities. <s> BIB004 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A hybrid hands-off human computer interface that uses infrared video eye gaze tracking (EGT) and electromyogram (EMG) signals is introduced. This system combines the advantages of both sub-systems, providing quick cursor displacement In long excursions and steady, accurate movement in small position adjustments. The hybrid system also provides a reliable clicking mechanism. The evaluation protocol used to test the system is described and the results for the hybrid, an EMG Only interface, and the standard hand-held mouse are described and compared. These results show that the hybrid system is, in an average, faster than the EMG-only system by a factor of 2 or more. <s> BIB005 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> The objective of this paper is to develop a powered wheelchair controller based on EMG for users with high-level spinal cord injury. EMG is very naturally measured when the user indicating a certain direction and the force information which will be used for the speed of wheelchair is easily extracted from EMG. Furthermore, the emergency situation based on EMG will be checked relatively ease. We classified the pre-defined motions such as rest case, forward movement, left movement, and right movement by fuzzy min-max neural networks (FMMNN). This classification results and evaluation results with real users shows the feasibility of EMG as an input interface for powered wheelchair. <s> BIB006 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body. <s> BIB007 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <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> BIB008 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> With the development of brain-computer interface (BCI) technology, researchers are now attempting to put current BCI techniques into practical application. This paper presents an environmental controller using a BCI technique based on steady-state visual evoked potential. The system is composed of a stimulator, a digital signal processor, and a trainable infrared remote-controller. The attractive features of this system include noninvasive signal recording, little training requirement, and a high information transfer rate. Our test results have shown that this system can distinguish at least 48 targets and provide a transfer rate up to 68 b/min. The system has been applied to the control of an electric apparatus successfully. <s> BIB009 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> Besides its clinical applications, various researchers have shown that EMG can be utilised in areas such as computer human interface and in developing intelligent prosthetic devices. The paper presents results from a preliminary study. The work describes the outcome in using an artificial neural network (ANN) to recognise and classify human speech based on EMG. The EMG signals were acquired from three articulatory facial muscles. Three subjects were selected and participated in the experiments. Preliminarily, five English vowels were used as recognition variables. The root mean square (RMS) values of the EMG signals were estimated and used as a set of features to feed the ANN. The findings indicate that such a system may have the capacity to recognise and classify speech signals with an accuracy of up to 88%. <s> BIB010 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A technique for improving the recognition accuracy of EMG-based speech recognition by applying existing speech recognition technologies is proposed. The authors have proposed an EMG-based speech recognition system that requires only mouth movements, voice need not be generated. A multi-stream HMM (hidden Markov model) and feature extraction technique are applied to EMG-based speech recognition. 3 channel facial EMG signals are collected from ten subjects when uttering 10 Japanese isolated digits. One channel corresponds to one stream. By examining various features, we found that the delta component of the static parameter leads to higher accuracy. Compared to equal stream weighting, the individual optimization of stream weights increased recognition accuracy by 4.0% which corresponds to a 12.8% reduction in error rate. This result shows that multistream HMM is effective for the classification of EMG. <s> BIB011 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two surface electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Four directional cursor movements ---up, down, right, and left--- and one selected operation were realized by logically combining the two detected channel signals based on threshold settings specific to the individual. Letter input experiments were conducted on a virtual screen keyboard. The method's usability was enhanced by minimizing the number of electrodes and applying training to both the subject and the device. As a result, an accuracy of 90.1 ± 3.6% and a processing speed of 7.7 ± 1.9 letters/min. were obtained using our method. <s> BIB012 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> In this paper we introduce a speech recognition system based on myoelectric signals. The system handles audible and non-audible speech. Major challenges in surface electromyography based speech recognition ensue from repositioning electrodes between recording sessions, environmental temperature changes, and skin tissue properties of the speaker. In order to reduce the impact of these factors, we investigate a variety of signal normalization and model adaptation methods. An average word accuracy of 97.3% is achieved using seven EMG channels and the same electrode positions. The performance drops to 76.2% after repositioning the electrodes if no normalization or adaptation is performed. By applying our adaptation methods we manage to restore the recognition rates to 87.1%. Furthermore, we compare audibly to non-audibly spoken speech. The results suggest that large differences exist between the corresponding muscle movements. Still, our recognition system recognizes both speech manners accurately when trained on pooled data <s> BIB013 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <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> BIB014 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A classification algorithm is developed to translate facial movements into five cursor actions: i) left, ii) right, iii) up, iv) down, and v) left-click. The algorithm utilizes the unique spectral characteristics exhibited by electromyogram (EMG) signals obtained from different muscles in the face to assist in the classification process. A previous three-electrode, EMG-based system was utilized in to perform a similar translation of facial movements into cursor actions. This system also made use of spectral analysis to classify muscle activity. It was found that this system does not always discriminate between the EMG activity assigned to up and down cursor actions efficiently. To remedy this matter, a fourth electrode was added and a new classification algorithm was devised. This paper details the classification algorithm utilized with the four-electrode system. It also compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions. This was done through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance <s> BIB015 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> At present, a three-input electromyography (EMG) system has been created to provide real-time, hands-free cursor control. The system uses the real-time spectral analysis of three EMG signals to produce the following five cursor actions: i) LEFT, ii) RIGHT, iii) UP, iv) DOWN, v) LEFT-CLICK. The three EMG signals are obtained from two surface electrodes placed on the left and right temples of the head and one electrode placed in the forehead region. The present system for translating EMG activity into cursor actions does not always discriminate between up and down EMG activity efficiently. To resolve this problem it was proposed that the three-electrode system be converted into a four-electrode system, using two electrodes in the forehead of the user, instead of one. This paper compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance. <s> BIB016 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A Coupled Hidden Markov Model (CHMM) is proposed in this paper to perform multimodal speech recognition using myoeletric signals (MES) from the muscles of vocal articulation. MES signals are immune to noise, and words that are acoustically similar manifest distinctly in MES. Hence, they would effectively complement the acoustic data in a multimodal speech recognition system. Research in Audio-Visual Speech Recognition has shown that CHMMs model the asynchrony between different data streams effectively. Hence, we propose CHMM for multimodal speech recognition using audio and MES as the two data streams. Our experiments indicate that the multimodal CHMM system significantly outperforms the audio only system at different SNRs. We have also provided a comparison between different features for MES and have found that wavelet features provide the best results. <s> BIB017 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> Purpose. This study develops a newly facial EMG human – computer interface for people with disabilities for controllng the movement of the cursor on a computer screen.Method. We access the computer cursor according to different facial muscle activity patterns. In order to exactly detect the muscle activity threshold, this study adopts continuous wavelet transformation to estimate the single motor unit action potentials dynamically.Result. The experiment indicates that the accuracy of using the facial mouse is greater than 80%, and this result indicates the feasibility of the proposed system. Moreover, the subject can improve performance of manipulation by repeated training.Conclusion. Compared with previous works, the proposed system achieves complete cursor function and provides an inexpensive solution. Although there are still some drawbacks in the facial EMG-based human – computer interface, the facial mouse can provide an alternative among other expensive and complicated assistive technologies. <s> BIB018 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> This paper describes an eye-gaze interface using a biological signal, electro-oculorgram (EOG). This interface enables a user to move a computer cursor on a graphical user interface using eye gaze movement alone. It will be useful as a communication aid for individuals with mobility handicaps. Although EOG is easily recordable, drifting and blinking problems must be solved to produce a reliable eye-gaze interface. Here we introduced a calibration method and a feedback control to overcome these problems. <s> BIB019 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Eight directional cursor movements and one selected operation were realized by logically combining the two detected channel signals based on threshold setting specific to the individuals. As experimental results using a projected screen keyboard, processing speed was improved to 12.1 letters/min. while the accuracy was 90.4%. <s> BIB020 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> Abstract Objective This study aimed to describe the use of the P300 event-related potential as a control signal in a brain computer interface (BCI) for healthy and paralysed participants. Methods The experimental device used the P300 wave to control the movement of an object on a graphical interface. Visual stimuli, consisting of four arrows (up, right, down, left) were randomly presented in peripheral positions on the screen. Participants were instructed to recognize only the arrow indicating a specific direction for an object to move. P300 epochs, synchronized with the stimulus, were analyzed on-line via Independent Component Analysis (ICA) with subsequent feature extraction and classification by using a neural network. Results We tested the reliability and the performance of the system in real-time. The system needed a short training period to allow task completion and reached good performance. Nonetheless, severely impaired patients had lower performance than healthy participants. Conclusions The proposed system is effective for use with healthy participants, whereas further research is needed before it can be used with locked-in syndrome patients. Significance The P300-based BCI described can reliably control, in ‘real time’, the motion of a cursor on a graphical interface, and no time-consuming training is needed in order to test possible applications for motor-impaired patients. <s> BIB021 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> We describe a study designed to assess properties of a P300 brain–computer interface (BCI). The BCI presents the user with a matrix containing letters and numbers. The user attends to a character to be communicated and the rows and columns of the matrix briefly intensify. Each time the attended character is intensified it serves as a rare event in an oddball sequence and it elicits a P300 response. The BCI works by detecting which character elicited a P300 response. We manipulated the size of the character matrix (either 3 � 3o r 6� 6) and the duration of the inter stimulus interval (ISI) between intensifications (either 175 or 350 ms). Online accuracy was highest for the 3 � 3 matrix 175-ms ISI condition, while bit rate was highest for the 6 � 6 matrix 175-ms ISI condition. Average accuracy in the best condition for each subject was 88%. P300 amplitude was significantly greater for the attended stimulus and for the 6 � 6 matrix. This work demonstrates that matrix size and ISI are important variables to consider when optimizing a BCI system for individual users and that a P300-BCI can be used for effective communication. # 2006 Elsevier B.V. All rights reserved. <s> BIB022 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> This paper outlines the development and initial testing of a new hybrid computer cursor control system based on Eye Gaze Tracking (EGT) and electromyogram (EMG) processing for hands-free control of the computer cursor. The ultimate goal of the system is to provide an efficient computer interaction mechanism for individuals with severe motor disabilities (or specialized operators whose hands are committed to other tasks, such as surgeons, pilots, etc.) The paper emphasizes the enhancements that have been made on different areas of the architecture, with respect to a previous prototype developed by our group, and demonstrates the performance improvement verified for some of the enhancements. <s> BIB023 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> Human-computer interactions (HCI) have become an important area of research and development in computer science and psychology. Appropriate use of computers could be of primary importance for communication and education of those subjects which could not move, speak, see or hear properly. The aim of our study was to develop a reliable, low-cost and easy-to-use HCI based on electrooculography signal analysis, to allow physically impaired patients to control a computer as assisted communication. Twenty healthy subjects served as volunteers: eye movements were captured by means of four electrodes and a two-channel amplifier. The output signal was then transmitted to an ''Analog to Digital'' (AD) converter, which digitized the signal of the amplifier at a rate of 500Hz, before being sent to a laptop. We designed and coded a specific software, which analyzed the input signal to give an interpretation of eye movements. By means of a single ocular movement (up, down, left and right) the subjects were then able to move a cursor over a screen keyboard, passing from one letter to another; a double eye blink was then necessary to select and write the active letter. After a brief training session, all the subjects were able to confidently control the cursor and write words using only ocular movements and blinking. For each subject we presented three series of randomized words: mean time required to enter a single character was about 8.5s, while input errors were very limited (less than 1 per 250 characters). Our results confirm those obtained in previous studies: eye-movement interface can be used to properly control computer functions and to assist communication of movement-impaired patients. <s> BIB024 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <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> BIB025 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> To address the issue of system simplicity and subject applicability, a brain controlled HCI system derived from steady state visual evoked potential (SSVEP) based brain computer interface (BCI) is proposed in this paper. Aiming at an external input device for personal computer, key issues of hardware and software design for better performance and user-friendly interface are introduced systematically. With proper parameter customization for each individual, an average information transfer rate of 46bits/min was achieved in the operation of dialing a phone number. With encouraging online performance and advantages of system simplicity, the proposed HCI using SSVEP-based BCI technology is promising for a substitute of standard computer input device for both health and disabled computer users. <s> BIB026 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model. <s> BIB027 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Conclusions <s> In this study, human subjects achieve two-dimensional cursor-to-target control using the surface electromyogram (sEMG) from a single muscle site. The X-coordinate and the Y-coordinate of the computer cursor were simultaneously controlled by the active manipulation of power within two frequency bands of the sEMG power-spectrum. Success of the method depends on the sEMG frequency bandwidths and their midpoints. We acquired the sEMG signals at a single facial muscle site of four able-bodied subjects and trained them, by visual feedback, to control the position of the cursor. After training, all four subjects were able to simultaneously control the X and Y positions of the cursor to accurately and consistently hit three widely-separated targets on a computer screen. This technology has potential application in a wide variety of human-machine interfaces to assistive technologies. <s> BIB028
In the last 20 years, driven by technical advances and government initiatives, assistive devices aimed to AAC increased enormously in number and variety. Access to AAC equipments can be made by means of electrical biosignals, which control is possible even for people with severe motor impairments. The EMG signal has the advantage of almost instantaneous response, and with four muscles available it is possible to establish control over a cursor. At first, it may not be very intuitive to move a cursor using, for instance, facial muscles. As studies indicate, diagonal movements are usually executed by horizontal and vertical displacements, but with increasingly user ability during training. The major caveat of using muscles is the fatigue that may impede prolonged time of activity. The number of muscles available varies greatly among patients with motor impairments, leading to a vast amount of strategies on using the EMG signal. For users with severe motor impairments it is expected that few muscles can be explored and therefore limiting the applications to scanning systems or cursor control in an unnatural way, as explained before. One possible improvement in the future is to develop signal processing algorithms that allow more reliable progressive signals encoding during contractions, what could improve dramatically performance of EMG-based AAC systems. The use of the EEG signals has gone by intensive research over the last two decades and has proved to be effective for various applications, as indicated by Wolpaw BIB004 . The BCI systems present high performance variability and present technical problems that must receive special attention, such as contamination by EMG signals. Additionally, BCI systems are not indicated to everyone, as there are people incapable of efficiently modulate brain waves. But since the head is the last site to suffer degradation in cases of severe disability, its use should be considered in extreme motor impairment conditions. The EOG signal has two advantages displayed by the two previous biosignals. As the EEG signal, the ability of a person to control biological process associated with the EOG signal is preserved even in extreme situations of motor impairment; and similar to the EMG signal, the EOG signal presents low response time. One of the applications of the EOG signal is cursor control task, although is generally deprecated when compared to gaze-based systems, that also use eye motion but spare the user the necessity of using electrodes attached to the skin. In fact, this last disadvantage is shared with the use of EEG and EMG signals, demanding proper skin preparation and electrodes placement, in what concerns position and possibly orientation. Dry electrodes adoption is an option, with electrical characteristics meeting the needs for recording electrical biosignal suitable to signal processing tools currently in use. The mechanical characteristics in the other hand, present the problem of higher mass when compared to gelled electrodes given the presence of pre-amplifier circuitry due to high electrode-skin impedance. The choice of the ideal solution for AAC is not trivial. It is well established that rehabilitation technologies deployment demands that each patient is analyzed individually. Unfortunately, there are few commercial devices available that explore electrical biosignals, and it is not probable that this picture is going to change in the short term. One of the reasons is the different degrees that the same condition (e.g. tetraplegia) afflicts different people, demanding not only user training but also user customization. For instance, in  the participant in a study for the deployment of a BCI was submitted to a functional magnetic resonance imaging (fMRI) to find the best sites to place electrodes. Beyond commercial approach, successfully adoption of the device depends on several factors, among them the caregiver ability to learn and personalize the new tool  . Therefore, it is necessary to close the gap between the knowledge required by the caregivers and the system complexity during set-up, support and training. Other considerations include aesthetics, as a device aiming for communication is likely to be used during social circumstances. Also, when idealizing the system, it should be considered the user effort in the operation of a device that ideally should be used for several hours a day. Most of the studies however, are conducted with patients only in the Phase I clinical trials, with few sessions per week, proving only the technical viability to transform electrical biosignals into commands, but failing in providing insights about the device operation in daily basis. Finally, assistive devices should have an operation principle as simple as possible. Solutions such as presented in BIB028 with a single muscle controlling the cursor position in two axes does not seem to be very easy to operate. In this case, the system complexity moved towards the user, which was obligated to execute an apparently hard task to achieve a simple operation. According to the 1990 U.S Census Bureau's National Health Interview Survey, about one-third of assistive devices not needed for survival are unused or abandoned just 3 months after they were initially acquired [6] . Nevertheless, some efforts of the world's scientific community for trying to change this paradigm and that are cited in this article, are synthesized in Table 1 . If factors such as aesthetics are subjective, the quantitative analysis of an AAC system is an objective and vital step in the choice for a given patient. It was observed that for the same task, i.e. cursor control, different measures are taken, preventing effective comparison of different sensors. The Fitts' law used to measure efficiency of pointing control device is a general accept method, and has even been used in the ISO 9241 norm for device evaluation, despite its adoption should be carefully analyzed as some solutions do not follow a "Fitts' law" approach. Despite the situation people with severe motor impairments are found, several solutions for AAC are available, exploring last abilities remaining. For instance, one person with tetraplegia at the C2 level may present control only from the neck up. Even though, all of the three biosignals addressed in this article could be explored by this user. Besides the user capability of using a given system, other considerations should be made, such as ergonomics, and also performance. An optimal choice of the control interface of an assistive device supposes an individualized assessment of the humanmachine interaction. For that it is often interesting to call upon models of humanmachine performance. Those interesting in our context of study are defined for a task or a category of tasks, for example Fitts' law for a pointing task, Hick's law for a choice of alternatives, MHP model for the simple motor reaction to a visual or an auditory stimulus. When we call upon this type of models, well established for people without disability, it is however essential to verify that they are adapted to the motor, perceptive and cognitive capacities of the person with disability concerned.  Morse code-based system controlled by sip-and-puff device. [27] Head motion detected by a motion sensor allows the user to control a cursor on the screen. Click and double click was performed by the user inflating the cheek and touching the switches. [90] Tilt sensors for cursor control. EMG BIB006 Device control such as wheelchairs, indicating the possibility of being used for AAC purposes.  BIB027 BIB010 BIB013 BIB011  Recorded from vocal articulation muscles, EMG signal features are used in the task of speech recognition. [19] EMG offers switch-based control signal used in a scanning system. [18] Morse code-based systems. BIB028 BIB018 BIB002 BIB003  Cursor control/pointing device established by EMG signals recorded from muscles that can be controlled by people with tetraplegia at the C4 level. EOG BIB024  A system for writing in an alphanumeric matrix based on two EOG channels (vertical and horizontal) BIB019 BIB020 BIB012 Cursor control by eye movement direction. [58] Eye movements are translated to Morse code symbols to issue command messages. [59] Sequences of eye movements are associated to symbols (10 Arabic numerals and 4 arithmetic operators). EEG BIB007  EEG (Mu and Beta rhythms) operate a 1D graphic device. [ BIB001  BIB025  BIB008  BIB021 BIB022  Language support controlling spelling systems. [74] Cursor control using spike activities detected by implanted electrodes BIB014  BIB009 BIB026 Device control such as appliances or a wheelchair, indicating the possibility of being used for AAC purposes Hybrid systems and others  Both EEG and EMG signals are applied to cursor control, including click. BIB004 BIB015 BIB016 EMG signals from facial muscles are used to control a cursor in 2D. The EEG signal acts as an ON/OFF switch. [100] Using a camera, the system tracks the computer user's movements to control the cursor on the screen. BIB023  BIB005 EOG signals define the absolute cursor position on the screen and EMG signals are used for small displacements. BIB017  EMG signals from muscles of vocal articulation are used to complement audio signals information in the task of speech recognition. [24] Cursor control system with the position controlled by gaze and the object selection activated by frowning. [30] Images and EMG signals are used to determine face position that can be used to intent expression. [49] Virtual keyboard writer system based on two EOG channels and one EMG channel for letter selection.