Biomedical subjects
Publications and source records attributed to G Pfurtscheller.
The Graz-brain-computer interface (BCI) is a cue-based system using the imagery of motor action as the appropriate mental task. Relevant clinical applications of BCI-based systems for control of a virtual keyboard device and operations of a hand orthosis are reported. Additionally, it is demonstrated how information transfer rates of 17 b/min can be acquired by real time classification of oscillatory activity.
Ninety-nine healthy people participated in a brain-computer interface (BCI) field study conducted at an exposition held in Graz, Austria. Each subject spent 20-30 min on a two-session BCI investigation. The first session consisted of 40 trials conducted without feedback. Then, a subject-specific classifier was set up to provide the subject with feedback, and the second session--40 trials in which the subject had to control a horizontal bar on a computer screen--was conducted. Subjects were instructed to imagine a right-hand movement or a foot movement after a cue stimulus depending on the direction of an arrow. Bipolar electrodes were mounted over the right-hand representation area and over the foot representation area. Classification results achieved with 1) an adaptive autoregressive model (39 subjects) and 2) band power estimation (60 subjects) are presented. Roughly 93% of the subjects were able to achieve classification accuracy above 60% after two sessions of training.
A "virtual keyboard" (VK) is a letter spelling device operated for example by spontaneous electroencephalogram (EEG), whereby the EEG 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.
The phenomena of event-related desynchronization (ERD) and synchronization (ERS) reflect the dynamics of neural networks and can be observed on different scalp locations at the same moment of time. Whereas on one cortical area a focal 10-Hz ERD can be found, other areas can display a 10-Hz ERS. This phenomenon is called focal ERD/surround ERS and is interpreted as a correlate of an activated cortical area (ERD) and simultaneously deactivated or inhibited other areas. The induced oscillations (ERS) are dominant in the 10- to 13-Hz band and very likely mediated by thalamic gating.
Electrical median nerve stimulation during rest results in two cortical responses: the somatosensory evoked potential (SEP); and the induced beta oscillations (beta event-related synchronization (ERS)). Both types of responses were recorded with electroencephalography and studied during rest and motor behavior in eight normal subjects. During manipulation of a cube with the fingers of the right hand, the beta ERS around 20 Hz, induced by right hand median nerve stimulation, is significantly suppressed, whereas the long-latency SEP components are significantly enhanced. The results suggest that both phenomena can be interpreted as responses of different neuronal structures in sensorimotor areas.
OBJECTIVES: Analysis of event-related desynchronization (ERD) and event-related synchronization (ERS) often requires the investigation of diverse frequency bands. Such analysis can be difficult, especially when using multichannel data. Therefore, an effective method for the visualization of event-related changes in oscillatory brain activity is required. METHODS: A bootstrap-based method is presented which gives time-frequency maps showing only significant changes of ERD or ERS in predetermined frequency bands. RESULTS: Examples from an electroencephalographic study and an electrocorticographic study are shown. The results demonstrate how easily reactive channels and their spatio-temporal and frequency-specific characteristics can be identified by means of this method. CONCLUSIONS: The proposed method is a simple but effective way to visualize significant ERD/ERS patterns.
A report is given on the realization of a steering mechanism of a hand orthosis for a patient with paraplegia. An EEG-based Brain-Computer Interface (BCI) was used here for the first time, transferring purely mental activity to a control signal. This means that the patient has the capability to open or close the hand orthosis only by imagination of a movement. At this time, after a training period of about four months, the patient is able to move the hand orthosis with a certainty of almost hundred percent. The restored grasp function was verified by a grasp function test. Results are compared to those obtained using a conventional EMG-controlled orthosis.
Induced beta oscillations were studied in three normal subjects after mechanical stimulation of each fingertip of the right hand. For stimulation short tactile stimuli of 10 ms duration were presented at intervals of 4 s. The electroencephalogram was recorded with 60 closely spaced electrodes and sampled at 256 Hz. For each subject the reactive beta band was determined by comparing 1-s power spectra. The largest beta power increase was found in the range of 12-28 Hz on electrodes overlying the left-hand area. The Matching Pursuit algorithm was applied to single trials data and the frequency of single "atoms" determined. In one subject the little finger showed a significant higher frequency as compared to the thumb. The difference in frequency was in the order of 1 Hz.
A new method is presented for the analysis of event-related EEG phenomena, in particular event related desynchronisation (ERD) and event related synchronisation (ERS) related to a voluntary movement; the method offers: high time-frequency resolution and, hence, increased ERD/ERS sensitivity (especially in the gamma band, where improvement can exceed an order of magnitude); the ability to analyse the whole picture of energy changes at once, without setting a priori the analysed frequency bands; and a parametric description of the signal's structures. The main idea is based upon averaging energy distributions of single EEG trials in the time-frequency plane. As the estimator for the signal's energy density, matching pursuit is chosen, with stochastic Gabor dictionaries. Other possible estimates are presented on a simulated signal and discussed briefly. The consistency of the results with previous findings is evaluated on the data from a classical voluntary finger movement experiment.
Sensory, cognitive and motor processing can result in changes of the ongoing EEG in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). Both phenomena are time-locked but not phase-locked to the event and they are highly frequency-band specific. The ERD is interpreted as a correlate of an activated cortical area with increased excitability and the ERS in the alpha and lower beta bands can be interpreted, at least under certain circumstances, as a correlate of a deactivated cortical area. Spatial mapping of ERD/ERS can be used to study the dynamics of cortical activation patterns. Examples from a movement task are reported.
EEG/MEG rhythmic activities such as alpha rhythms, of the visual or of the somato-sensory cortex, are commonly modulated as subjects perform certain tasks or react to specific stimuli. In general, these activities change depending on extrinsic or intrinsic events. A decrease of the amplitude of alpha rhythmic activity occurring after a given event, which manifests as a decrease of a spectral peak, is called event-related desynchronization (ERD), whereas the inverse is called event-related synchronization (ERS), since it is assumed that the power of a spectral peak is related to the degree of synchrony of the underlying oscillating neuronal populations. An intriguing observation in this respect [Pfurtscheller and Neuper, Neurosci. Lett. 174 (1994) 93-96] was that ERD of alpha rhythms recorded over the central areas was accompanied by ERS, within the same frequency band, recorded over neighboring areas. In case the event was a hand movement, ERD was recorded over the scalp overlying the hand cortical area, whereas ERS was concomitantly recorded over the midline, whereas if the movement was of the foot the opposite was found. We called this phenomenon 'focal ERD/surround ERS'. The question of how this phenomenon may be generated was approached by means of a computational model of thalamo-cortical networks, that incorporates basic properties of neurons and synaptic interactions. These simulation studies revealed that this antagonistic ERD/ERS phenomenon depends on the functional interaction between the populations of thalamo-cortical cells (TCR) and reticular nucleus cells (RE) and on how this interaction is modulated by cholinergic inputs. An essential feature of this interaction is the existence of cross-talk between different sectors of RE that correspond to distinct sensory modules (e.g. hand, foot). These observations led us to formulate the hypothesis that this basic neurophysiological mechanism can account for the general observation that enhanced attention given to a certain stimulus (the focus) is coupled to inhibition of attention to other stimuli (the surround).
Oscillations in the alpha and beta band (<35 Hz) display a dynamic behavior and show characteristic spatiotemporal patterns in sensory, motor and cognitive tasks. The event-related desynchronization (ERD) of alpha band and beta rhythms can be seen as a correlate of an activated cortical area with an increased excitability level of neurons. An event-related synchronization (ERS) of frequency components between 10 and 13 Hz may represent a deactivated cortical area or inhibited cortical network, at least under certain circumstances. It is hypothesized, that antagonistic ERD/ERS patterns, called 'focal ERD/surround ERS', may reflect a thalamo-cortical mechanism to enhance focal cortical activation by simultaneous inhibition of other cortical areas. Induced oscillations in the beta band (13-35 Hz, beta ERS) were found in sensorimotor areas after voluntary movement and after somatosensory stimulation. This may be interpreted as a state of 'inhibition' of neural circuitry in the primary motor cortex. Simultaneous activation of the motor cortex by e.g. motor imagery lead to an attenuation of the beta ERS. Moreover, there is evidence that the frequency of the induced beta oscillations represent a 'resonance-like frequency' of underlying cortical networks. However, further research is needed to investigate the functional meaning of bursts of beta oscillations below 35 Hz.
OBJECTIVE: We studied event-related synchronization (ERS) of beta rhythms related to voluntary movement vs. stimulation of upper and lower limbs. The aim of this study was to investigate whether the frequency of the beta response is related to specific regions within the sensorimotor strip. METHODS: Self-paced movement and electrical stimulation of the dominant hand and foot/leg was investigated in 10 right-handed volunteers. The electroencephalogram was recorded from closely spaced electrodes over central areas and processed time-locked to movement-offset or stimulation. In order to identify the dominant frequency of the induced beta oscillations, time-frequency maps were calculated using the continuous wavelet transformation. For the specific beta frequency bands, the band power time courses were analyzed by quantifying the event-related (de-)synchronization (ERD/ERS). RESULTS: Both limb movement and somatosensory stimulation induced bursts of beta oscillations appearing within 1 s after movement/stimulation with a clear focus close to the corresponding sensorimotor representation area. The peak frequency was significantly lower over the hand area (below approximately 20 Hz) than at mid-central sites overlying the foot representation area (above approximately 20 Hz). But no difference was found between movement and stimulation of the respective limb. CONCLUSIONS: Analyzing the frequency of induced beta activity revealed concomitant oscillations at slightly different frequencies over neighboring cortical areas. These oscillations might be indicative for a resonance-like behavior of connected sub-networks in sensorimotor areas.
Short mechanical stimulation of the fingertip was studied in 10 subjects using 34 closely spaced EEG electrodes overlying sensorimotor areas. The tactile skin stimulation device consisted of a dot matrix printer head. Each stimulus lasted 10 msec with an interstimulus interval of 4 seconds. Tactile stimulation induced beta oscillations, which were largest in the 16 to 20-Hz band, with a maximum centered within 1 second after stimulation. These beta oscillations were found over both hemispheres with a clear dominance over the contralateral hand representation area.
Intention of movement of left or right index finger, or right foot is recognized in electroencephalograms (EEGs) from three subjects. We present a multichannel classification method that uses a "committee" of artificial neural networks to do this. The classification method automatically finds spatial regions on the skull relevant for the classification task. Depending on subject, correct recognition of intended movement was achieved in 75%-98% of trials not seen previously by the committee, on the basis of single EEGs of one-second duration. Frequency filtering did not improve recognition. Classification was optimal during the actual movement, but a first peak in the classification success rate was observed in all subjects already when they had been cued which movement later to perform.
The electroencephalogram (EEG) is modified by motor imagery and can be used by patients with severe motor impairments (e.g., late stage of amyotrophic lateral sclerosis) to communicate with their environment. Such a direct connection between the brain and the computer is known as an EEG-based brain-computer interface (BCI). This paper describes a new type of BCI system that uses rapid prototyping to enable a fast transition of various types of parameter estimation and classification algorithms to real-time implementation and testing. Rapid prototyping is possible by using Matlab, Simulink, and the Real-Time Workshop. It is shown how to automate real-time experiments and perform the interplay between on-line experiments and offline analysis. The system is able to process multiple EEG channels on-line and operates under Windows 95 in real-time on a standard PC without an additional digital signal processor (DSP) board. The BCI can be controlled over the Internet, LAN or modem. This BCI was tested on 3 subjects whose task it was to imagine either left or right hand movement. A classification accuracy between 70% and 95% could be achieved with two EEG channels after some sessions with feedback using an adaptive autoregressive (AAR) model and linear discriminant analysis (LDA).
The information transfer rate, given in bits per trial, is used as an evaluation measurement in a brain-computer interface (BCI). Three subjects performed four motor-imagery (left hand, right hand, foot, and tongue) and one mental-calculation task. Classification of the electroencephalogram (EEG) patterns is based on band power estimates and hidden Markov models (HMMs). We propose a method that combines the EEG patterns based on separability into subsets of two, three, four, and five mental tasks. The information transfer rates of the BCI systems comprised of these subsets are reported. The achieved information transfer rates vary from 0.42 to 0.81 bits per trial and reveal that the upper limit of different mental tasks for a BCI system is three. In each subject, different combinations of three tasks resulted in the best performance.
The aim of the present study was to investigate whether self-induced brain potential changes could be useful as control signals for patients with severe motor impairment, i.e. due to high-level spinal cord injury. The pilot project was performed in a tetraplegic patient (T.S.), whose residual muscle activity of the upper limbs is restricted to the left biceps. To restore the hand grasp function, an electrical driven hand orthosis fitting his left hand was developed. The operation of this device is directly based on the bioelectrical signals of the brain. After some months of training, T. S. has learned to operate the hand orthosis by mental imagination of specific motor commands.