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Rehabilitation Engineering, IEEE Transactions on

Issue 2 • Date Jun 2000

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Displaying Results 1 - 22 of 22
  • A natural basis for efficient brain-actuated control

    Page(s): 208 - 211
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    The prospect of noninvasive brain-actuated control of computerized screen displays or locomotive devices is of interest to many and of crucial importance to a few `locked-in' subjects who experience near total motor paralysis while retaining sensory and mental faculties. Currently several groups are attempting to achieve brain-actuated control of screen displays using operant conditioning of particular features of the spontaneous scalp electroencephalogram (EEG) including central μ-rhythms (9-12 Hz). A new EEG decomposition technique, independent component analysis (ICA), appears to he a foundation for new research in the design of systems for detection and operant control of endogenous EEG rhythms to achieve flexible EEG-based communication. ICA separates multichannel EEG data into spatially static and temporally independent components including separate components accounting for posterior alpha rhythms and central μ activities. The authors demonstrate using data from a visual selective attention task that ICA-derived μ-components can show much stronger spectral reactivity to motor events than activity measures for single scalp channels, ICA decompositions of spontaneous EEG would thus appear to form a natural basis for operant conditioning to achieve efficient and multidimensional brain actuated control in motor-limited and locked-in subjects View full abstract»

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  • EEG-based communication: a pattern recognition approach

    Page(s): 214 - 215
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    Presents an overview of the authors' research into brain-computer interfacing (BCI). This comprises an offline study of the effect of motor imagery on EEG and an online study that uses pattern classifiers incorporating parameter uncertainty and temporal information to discriminate between different cognitive tasks in real-time View full abstract»

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  • A virtual reality testbed for brain-computer interface research

    Page(s): 188 - 190
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    Virtual reality promisers to extend the realm of possible brain-computer interface (BCI) prototypes. Most of the work using electroencephalograph (EEG) signals in VR has focussed on brain-body actuated control, where biological signals from the body as well as the brain are used. The authors show that when subjects are allowed to move and act normally in an immersive virtual environment, cognitive evoked potential signals can still be obtained and used reliably. A single trial accuracy average of 85% for recognizing the differences between evoked potentials at red and yellow stop lights is presented and future directions discussed View full abstract»

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  • Current trends in Graz brain-computer interface (BCI) research

    Page(s): 216 - 219
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    Describes a research approach to develop a brain-computer interface (BCI) based on recognition of subject-specific EEG patterns. EEG signals recorded from sensorimotor areas during mental imagination of specific movements are classified on-line and used e.g. for cursor control. In a number of on-line experiments, various methods for EEG feature extraction and classification have been evaluated View full abstract»

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  • A direct brain interface based on event-related potentials

    Page(s): 180 - 185
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    Cross-correlation between a trigger-averaged event-related potential (ERP) template and continuous electrocorticogram was used to detect movement-related ERP's. The accuracy of ERP detection for the five best subjects (of 17 studied), had hit percentages >90% and false positive percentages <10%. These cases were considered appropriate for operation of a direct brain interface View full abstract»

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  • The thought translation device (TTD) for completely paralyzed patients

    Page(s): 190 - 193
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    The thought translation device trains locked-in patients to self regulate slow cortical potentials (SCP's) of their electroencephalogram (EEG). After operant learning of SCP self control, patients select letters, words or pictograms in a computerized language support program. Results of five respirated, locked-in-patients are described, demonstrating the usefulness of the thought translation device as an alternative communication channel in motivated totally paralyzed patients with amyotrophic lateral sclerosis View full abstract»

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  • Brain-computer interface research at the Wadsworth Center

    Page(s): 222 - 226
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    Studies at the Wadsworth Center over the past 14 years have shown that people with or without motor disabilities can learn to control the amplitude of μ or β rhythms in electroencephalographic (EEG) activity recorded from the scalp over the sensorimotor cortex and can use that control to move a cursor on a computer screen in one or two dimensions. This EEG-based brain-computer interface (BCI) could provide a new augmentative communication technology for those who are totally paralyzed or have other severe motor impairments, Present research focuses on improving the speed and accuracy of BCI communication View full abstract»

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  • Linear classification of low-resolution EEG patterns produced by imagined hand movements

    Page(s): 186 - 188
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    Electroencephalograph (EEG)-based brain-computer interfaces (BCI's) require on-line detection of mental states from spontaneous EEG signals, In this framework, surface Laplacian (SL) transformation of EEG signals has proved to improve the recognition scores of imagined motor activity. The results the authors obtained in the first year of an European project named adaptive brain interfaces (ABI) suggest that: (1) the detection of mental imagined activity can be obtained by using the signal space projection (SSP) method as a classifier and (2) a particular type of electrodes can be used in such a BCI device, reconciling the benefits of SL waveforms and the need for the use of few electrodes. Recognition of mental activity was attempted on both raw and SL-transformed EEG data from five healthy people performing two mental tasks, namely imagined right and left hand movements View full abstract»

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  • Work toward real-time control of a cortical neural prothesis

    Page(s): 196 - 198
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    Implantable devices that interact directly with the human nervous system have been gaining acceptance in the field of medicine since the 1960's. More recently, as is noted by the FDA approval of a deep brain stimulator for movement disorders, interest has shifted toward direct communication with the central nervous system (CNS). Deep brain stimulation (DBS) can have a remarkable effect on the lives of those with certain types of disabilities such as Parkinson's disease, Essential Tremor, and dystonia. To correct for many of the motor impairments not treatable by DBS (e.g. quadriplegia), it would be desirable to extract from the CNS a control signal for movement. A direct interface with motor cortical neurons could provide an optimal signal for restoring movement. In order to accomplish this, a real-time conversion of simultaneously recorded neural activity to an online command for movement is required. A system has been established to isolate the cellular activity of a group of motor neurons and interpret their movement-related information with a minimal delay. The real-time interpretation of cortical activity on a millisecond time scale provides an integral first step in the development of a direct brain-computer interface (BCI) View full abstract»

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  • Parallel man-machine training in development of EEG-based cursor control

    Page(s): 203 - 205
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    A new parallel man-machine training approach to brain-computer interface (BCI) succeeded through a unique application of machine learning methods. The BCI system could train users to control an animated cursor on the computer screen by voluntary electroencephalogram (EEG) modulation. The authors' BCI system requires only two to four electrodes, and has a relatively short training time for both the user and the machine. Moving the cursor in one dimension, the authors' subjects were able to hit 100% of randomly selected targets, while in two dimensions, accuracies of approximately 63% and 76% was achieved with the authors' two subjects View full abstract»

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  • Nerve cuff recordings of muscle afferent activity from tibial and peroneal nerves in rabbit during passive ankle motion

    Page(s): 244 - 258
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    Activity from muscle afferents regarding ankle kinesthesia was recorded using cuff electrodes in a rabbit preparation in which tactile input from the foot was eliminated. The purpose was to determine if such activity can provide information useful in controlling functional electrical stimulation (FES) systems that restore mobility in spinal injured man. The rabbit's ankle was passively flexed and extended while the activity of the tibial and peroneal nerves was recorded. Responses to trapezoidal stimulus profiles were investigated for excursions from 100 to 600 using velocities from 50/s to 300/s and different initial ankle positions. The recorded signals mainly reflect activity from primary and secondary muscle afferents. Dorsiflexion stretched the ankle extensors and produced velocity dependent activity in the tibial nerve, and this diminished to a tonic level during the stimulus plateau. The peroneal nerve was silent during dorsiflexion, but was activated by stretch of the peroneal muscles during ankle extension. The responses of the two nerves behaved in a reciprocal manner, hut exhibited considerable hysteresis, since motion that relaxed the stretch to the driving muscle produced an immediate cessation of the prior stretch induced activity. A noted difference between the tibial and peroneal nerve responses is that the range of joint position change that activated the flexor afferents was greater then for the extensor afferents. Ankle rotation at higher velocities increased the dynamic stretch evoked responses during the stimulus ramp but showed no effect on the tonic activity during the stimulus plateau. Prestretching the muscles by altering the initial position increased the response to the ramp movement, however, for the peroneal nerve, when the prestretch brought the flexor muscles near to their maximal lengths, the response to additional stretch provided by the ramp movement was diminished. The results indicate that the whole nerve recorded muscle afferent activity may be useful for control of FES assisted standing, because it can indicate the direction of rotation of the passively moved ankle joint, along with coarse information regarding the rate of movement and static joint position View full abstract»

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  • Applications of cortical signals to neuroprosthetic control: a critical review

    Page(s): 205 - 208
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    Cortical signals might provide a potential means of interfacing with a neuroprosthesis. Guidelines regarding the necessary control features in terms of both performance characteristics and user requirements are presented, and their implications for the design of a first generation cortical control interface for a neuroprosthesis are discussed View full abstract»

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  • Direct control of a computer from the human central nervous system

    Page(s): 198 - 202
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    Describes an invasive alternative to externally applied brain-computer interface (BCI) devices. This system requires implantation of a special electrode into the outer layers of the human neocortex. The recorded signals are transmitted to a nearby receiver and processed to drive a cursor on a computer monitor in front of the patient. The authors' present patient has learned to control the cursor for the production of synthetic speech and typing View full abstract»

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  • Cycling by means of functional electrical stimulation

    Page(s): 233 - 243
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    The goal of this paper was the development of an optimized stimulation pattern of leg muscles that would allow paraplegic subjects to perform the movement of pedaling and thereby to drive a tricycle by means of functional electrical stimulation (FES). To obtain maximum average power output with minimum muscle force, the start, duration and amplitude of the stimulation signal applied to the individual muscles had to be optimized depending on the pedaling frequency. For the basic theoretical investigations the rider-tricycle system was modeled as a rigid body system on which the muscle forces are applied as joint moments. The muscles gluteus maximus, rectus femoris, vastii, and hamstrings were stimulated and the passive forces of some other muscles were considered. The modeling and simulation approach was then used to produce maximum power pedaling and steady-state pedaling at 35 rpm. Hamstrings (41.9 %) and vastii (35.8 %) were the primary contributors to the optimization cost function of maximum power with minimum muscle loading. Based on these theoretical investigations an efficient stimulation pattern could be provided, taking into account the realistic possibilities of today's practical applications View full abstract»

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  • Brain-computer interfaces based on the steady-state visual-evoked response

    Page(s): 211 - 214
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    The Air Force Research Laboratory has implemented and evaluated two brain-computer interfaces (BCI's) that translate the steady-state visual evoked response into a control signal for operating a physical device or computer program. In one approach, operators self-regulate the brain response; the other approach uses multiple evoked responses View full abstract»

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  • The afferent neural response to electrotactile stimuli: preliminary results

    Page(s): 268 - 270
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    The authors recorded action potentials from three RA fibers innervating primate fingerpad, while applying electrotactile (electrocutaneous) stimulation. Negative pulses required 1.3-1.5 times more current than positive ones for entrainment. The strength-duration time constant was approximately 151 μs. Suprathreshold sinusoidal vibration synchronized to 30-Hz electrotactile pulses changed the electrotactile entrainment current slightly, indicating a possible electrical-mechanical transduction interaction View full abstract»

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  • Brain-computer interface research at the Neil Squire Foundation

    Page(s): 193 - 195
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    The ultimate goal of the authors' research is to utilize voluntary motor-related potentials recorded from the scalp in a direct Brain Computer Interface for asynchronous control applications. This type of interface will allow an individual with a high-level impairment to have effective and sophisticated control of devices such as wheelchairs, robotic assistive appliances, computers, and neural prostheses View full abstract»

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  • The mental prosthesis: assessing the speed of a P300-based brain-computer interface

    Page(s): 174 - 179
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    Describes a study designed to assess a brain-computer interface (BCI), originally described by Farwell and Donchin in 1988. The system utilizes the fact that the rare events in the oddball paradigm elicit the P300 component of the event-related potential (ERP). The BCI presents the user with a matrix of 6 by 6 cells, each containing one letter of the alphabet. The user focuses attention on the cell containing the letter to be communicated while the rows and the columns of the matrix are intensified. Each intensification is an event in the oddball sequence, the row and the column containing the attended cell are “rare” items and, therefore, only these events elicit a P300. The computer thus detects the transmitted character by determining which row and which column elicited the P300. The authors report an assessment, using a bootstrapping approach, which indicates that an off line version of the system can communicate at the rate of 7.8 characters a minute and achieve 80% accuracy. The system's performance in real time was also assessed. The authors' data indicate that a P300-based BCI is feasible and practical. However, these conclusions are based on tests using healthy individuals View full abstract»

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  • A binary spelling interface with random errors

    Page(s): 227 - 232
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    An algorithm for design of a spelling interface based on a modified Huffman's algorithm is presented. This algorithm builds a full binary tree that allows to maximize an average probability to reach a leaf where a required character is located when a choice at each node is made with possible errors. A means to correct errors (a delete-function) and an optimization method to build this delete-function into the binary tree are also discussed. Such a spelling interface could be successfully applied to any menu-orientated alternative communication system when a user (typically, a patient with devastating neuromuscular handicap) is not able to express an intended single binary response, either through motor responses or by using of brain-computer interfaces, with an absolute reliability View full abstract»

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  • Quantitative evaluation of two methods of control bilateral stimulated hand grasps in persons with tetraplegia

    Page(s): 259 - 267
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    Electrical stimulation has been applied to the paralyzed muscles of both hands of two persons with tetraplegia using percutneous acid implantable electrodes. Two separate methods of user control were being investigated. The first monitored the myoelectric signals from the user's own sternocleidomastoid muscles and the second monitored wrist joint angle. These signals were used as commands to modify the stimulated grasps. The hands were instrumented to detect the degree of hand closure and grip force and the users matched these to specific target parameters using the controller during tracking tasks. Performance in these tracking tasks was measured quantitatively. Wrist control was found to be less sensitive to the direction of hand opening/closing required than the myoelectric control. The user's performance with the myoelectric control demonstrated sensitivity to the target size and the speed of hand movement in response to the command control. The wrist controller required less training than the myoelectric controller for users to become proficient in its use. Based on these results, the wrist controller and the myoelectric controller both provide successful control of bilateral hand grasp and release. Of the two controllers, the wrist controller is likely to provide the greater ease of use, although it is only available to the population of users with active wrist extension View full abstract»

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  • The effects of self-movement, observation, and imagination on μ rhythms and readiness potentials (RP's): toward a brain-computer interface (BCI)

    Page(s): 219 - 222
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    Current movement-based brain-computer interfaces (BCI's) utilize spontaneous electroencephalogram (EEG) rhythms associated with movement, such as the μ rhythm, or responses time-locked to movements that are averaged across multiple trials, such as the readiness potential (RP), as control signals. In one study, the authors report that the μ rhythm is not only modulated by the expression of self-generated movement but also by the observation and imagination of movement. In another study, the authors show that simultaneous self-generated multiple limb movements exhibit properties distinct from those of single limb movements. Identification and classification of these signals with pattern recognition techniques provides the basis for the development of a practical BCI. View full abstract»

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Aims & Scope

This Transaction ceased publication in 2000. The current retitled publication is IEEE Transactions on Neural Systems and Rehabiliation Engineering.

Full Aims & Scope