Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <s> The discrete movement task employed in this study consisted of moving a cursor from the center of a computer display screen to circular targets located 24.4 and 110.9 mm in eight radial directions. The target diameters were 2.7, 8.1, and 24.2 mm. Performance measures included movement time, cursor path distance, and root-mean-square cursor deviation. Ten subjects with no movement disabilities were studied using a conventional mouse and a lightweight ultrasonic head-controlled computer input pointing device <s> BIB001 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> Mouse emulation <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> Mouse emulation <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> Mouse emulation <s> This research reports on the development of a headset-type position sensors-controlled computer mouse for the disabled. This system may serve to assist those who suffer from spinal cord injuries or other handicaps to operate a computer. This system is composed of three major components: (A) the position sensor module; (B) the signal-processing module; and (C) a main controller, the Intel-8951 microprocessor. This concept of design is mainly based on the idea that the use of the position sensor module fastened to the headset could allow the convenient control of the operation of a computer mouse. Through this system, the disabled are competent for some types of work, such as a computer operator. The increase of opportunity to do a job for the disabled would help them live independently. <s> BIB005 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB006 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <s> The paralytic caused by the high-level spinal cord injury needs a human-computer interface (HCI) for expressing their intention. In this paper, we propose a novel method to estimate face direction angle using both image observation and electromyogram (EMG) signal from neck muscles. The EMG signal to neck muscle is linear to the face direction angle, but it is undetectable in relatively small angle. Using the image observation, the small face angle is estimated by the geometric relationship between pupils and the face. If two measurements obtained by the EMG signal and the image observation are available, the face direction angle is estimated accurately by a linear interpolation method. We implemented a camera viewing direction control system using the face direction interface, and showed that the proposed method can be used to construct an HCI system for the disabled people with severe motor disabilities. <s> BIB007 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <s> The present aim was to study a new technique for human--computer interaction. It combined the use of two modalities, voluntary gaze direction and voluntary facial muscle activation for object pointing and selection. Fourteen subjects performed a series of pointing tasks with the new technique and with a mouse. At short distances the mouse was significantly faster than the new technique. However, there were no statistically significant differences at medium and long distances between the techniques. Fitts' law analyses were performed both by using only error-free trials and using also data including error trials (i.e., effective target width). In all cases both techniques seemed to follow Fitts' law, although for the new technique the effective target width correlation coefficient was smaller R = 0.776 than for the mouse R = 0.991. The regression slopes suggested that at very long distances (i.e., beyond 800 pixels) the new technique might be faster than the mouse. The new technique showed promising results already after a short practice and in the future it could be useful especially for physically challenged persons. <s> BIB008 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB009 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB010 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB011 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB012 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <s> We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, electromyography (EMG) from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2-D, center-out, Fitts' Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with somewhat lower performance. EMG commanded movements exhibited a higher average speed, but other performance measures were lower, particularly for diagonal targets. Compared to head orientation, EMG as a cursor command source was less accurate, was more affected by target direction and was more prone to overshoot the target. In particular, EMG commands for diagonal targets were more sequential, moving first in one direction and then the other rather than moving simultaneous in the two directions. While the relative performance of each user interface differs, each has specific advantages depending on the application. <s> BIB013 </s> Alternative communication systems for people with severe motor disabilities: a survey <s> Mouse emulation <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> BIB014
Since the 1970s the mouse is, along with the keyboard, the standard input device for computers operation. Then, it is understandable the number of studies to develop devices that provide mainly point-and-click functions as a physical keyboard can be replaced by a virtual one. For some studies, even though the goal is to provide a hands-free alternative to healthy people, the solution could be adapted for the person with disability. Using muscles in the pointing task can be described as a three-step process: (i) identifying the suitable muscles to be explored and based on this, (ii) define what kind of control can be obtained and (iii) last, choose and process the EMG signal feature to generate the command. In the case of people with severe motor disabilities, facial muscles are a common option as they can be activated, even in the case of people who suffered a severe spinal cord injury. Once the number of muscles available has been established, research can start to set up the strategy to achieve proper cursor control. One simple strategy is to use each muscle to define the cursor displacement in one direction. There are at least two aspects that will define the system final capacity to control a cursor: the sensor type and the user ability to control the muscles. If a PRO sensor is used and the user has the dexterity necessary to control all the four muscles at once, the cursor control will be omnidirectional. If an SBC sensor is employed with the same user, than the cursor can moves towards eight different directions. Finally, if the SBC sensor is operated by someone with poor muscle control, it is likely that the cursor will move to only four different directions. The most commonly used facial muscles in the pointing task are the Corrugator, the left and right Frontalis, the left and right Temporalis and the left and right Zygomaticus major. Traditional approaches use pairs of muscles to control displacement over the XY axis. Others strategies for exploring the EMG signal are possible, such as the 2D control from only one BIB014 muscle. Considering all the actions a mouse can perform there are also right and left-clicks. In BIB004 the left-click action and cursor movement (2D) were controlled by the EMG signals from the Temporalis and Frontalis muscles. Additionally, the system is provided with an ON/OFF switch, controlled by the EEG signal. The mouse functions were identified applying a threshold to the amplitude signal, and later, performing spectral analysis over several frequency bands. The system was implemented over a DSP board, which was identified by the host as an ordinary mouse. The final command information generated from the EMG signals was not actually continuous as the application may suggest. Actually, the system used a three-level adjustable speed schema, with increasing values if the system identified five consecutive commands indicating the same direction. At first, only three channels for EMG signals were necessary, but in BIB009 BIB010 a fourth electrode was used, improving the average of correct classification of muscle movements from 78.43% to 98.42%. Despite the good results for classification muscle movements, the system took 16.3s in average to move a cursor from the middle to the corner of the screen, compared to 1s-2s with a standard mouse. So, in BIB011  BIB006 the same approach was combined with a gaze-based system into a hybrid system. While the gaze offered the absolute position of the cursor, the EMG signal provided incremental displacement. As consequence, the time to move a cursor from the middle to the corner of the screen dropped from 16.3s to 6.8s. Also considering multimodal approaches, a detailed study BIB008 compared a standard mouse and a hybrid device. The cursor position was controlled by gaze and the object selection (left-click) was activated by frowning. The two solutions were compared using Fitts' law: for small distances a standard mouse showed superior performance, but there was no statistical difference among devices with large distances. In BIB012 the goal was also to provide a pointing device controlled by facial muscles. A continuous Wavelet transform measured the level of activation of each muscle, providing four direction displacements, associated with both sides of Orbicular, Massetter and Mentalis muscles. Left and right click operations were associated to opposite directions executed at the same time (Up+Down = right click and Left+Right = left click). The use of the Wavelet transform was justified by the shape similarity between the wavelet mother and the MUAPs. However, this strategy can be questioned, as the system performance was not compared with traditional signal features (e.g. the RMS value). Even the similarity between the Wavelet mother and the MUAPs can't be assured, as no other arbitrary wavelet mother was used and the electrodes dimensions were not reported, being impossible to estimate the electrodes selectivity regarding muscle units. Using four muscles to control horizontal and vertical displacement seems like a very straightforward idea. Nevertheless, in a novel approach BIB014 the authors employed only one muscle to control the cursor position in the X and Y axis. The power levels of two different frequency bands extracted from the EMG signal recorded from the Auricularis Superior muscle were employed. The strategy adopted is quite different from the others described earlier, as the absence of muscle activity sets the cursor the position to coordinates (0,0) while the contraction moves the cursor. The user training is mandatory, as not only the user should learn how the contractions affected the cursor position, but also because of the different bands of interest presented by different users. For patients unable of controlling upper limbs, using muscles located in the head may be the only option. However, people with conditions such as tetraplegia may manifest residual control of neck, shoulders and even arms. Additionally, using facial muscles seems as an unnatural way of controlling a cursor, when comparing to a standard mouse. As example, diagonal movements tend to be accomplished through horizontal and vertical movements BIB013 when using EMG signals as source of control. Head motion BIB005 , on the other hand, could be compared to a joystick operation. In BIB002 BIB003 , five different motions of neck and shoulder could be recognized with 95% mean recognition rate and response time about 0.17s. Two pairs of electrodes were placed over the Sternocleidomastoid and the Trapezius muscles, in each side of the body. In BIB013 three methods offering pointing device control were compared: a standard mouse, head-orientation using an accelerometer and the EMG based approach. The Platysma, left Trapezius and the Frontalis muscles were utilized. Cursor speed was a continuous variable, with a maximum value attributed to 70% of maximum voluntary contraction (MVC). As expected, the mouse was superior and in general the EMG approach was inferior to the head-orientation method, especially due the difficulty to perform diagonal movements. In BIB007 the angle of head was estimated through linear interpolation of the EMG signal extracted from the Sternocleidomastoid muscle. For small angle rotations the EMG signal is too small to offer any useful information and in its place a camera was used and the angle was estimated by the relative position of the pupils. In fact, if the user presents good head and neck control, the camera based solution seems to be more appropriated, with software already available for download, demanding only an ordinary webcam. Finally, there is the possibility to use movements of arms to operate virtual keyboards and mouse. In  an omnidirectional pointing device is controlled by the EMG signals recorded from the forearm. An Artificial Neural Network (ANN) was used to find the direction, while the muscular contraction level controlled the cursor velocity. A recent research involving the Microsoft Corporation presents a similar approach using the EMG signal in games  interfaces but also in hands-busy situations, that could also be deployed for people presenting some level of disability. The implication of a company highly bounded with the computing area indicates the potential of using the EMG signal for computing interface. However, solutions for user presenting good arm movement control are outside the scope of this article and even in the case of adopting an assistive device, adapted mouse or joysticks would be more appropriated for this user profile. It was noticed that some studies lack a method to measure performance, impeding therefore the comparison of different approaches. Fitts' Law was already used to compare different pointing devices BIB001 and has been used in several studies; precision on drawing over templates are also suggested  . The methods used for performance measure are presented in details in section 6. Other problem with pointing devices studies is that details such as screen resolution and specifications of the standard mouse used are not revealed.