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Biomedical subjects

G Pfurtscheller

Publications and source records attributed to G Pfurtscheller.

At least 73 records · Page 4Linked to original sources
PubMed1999

Frequency component selection for an EEG-based brain to computer interface.

A new communication channel for severely handicapped people could be opened with a direct brain to computer interface (BCI). Such a system classifies electrical brain signals online. In a series of training sessions, where electroencephalograph (EEG) signals are recorded on the intact scalp, a classifier is trained to discriminate a limited number of different brain states. In a subsequent series of feedback sessions, where the subject is confronted with the classification results, the subject tries to reduce the number of misclassifications. In this study the relevance of different spectral components is analyzed: 1) on the training sessions to select optimal frequency bands for the feedback sessions and 2) on the feedback sessions to monitor changes.

Adult↗
PubMed1999

Hidden Markov models used for the offline classification of EEG data.

Hidden Markov models (HMM) are introduced for the offline classification of single-trail EEG data in a brain-computer-interface (BCI). The HMMs are used to classify Hjorth parameters calculated from bipolar EEG data, recorded during the imagination of a left or right hand movement. The effects of different types of HMMs on the recognition rate are discussed. Furthermore a comparison of the results achieved with the linear discriminant (LD) and the HMM, is presented.

Biofeedback, Psychology↗
PubMed1998

Feature extraction for on-line EEG classification using principal components and linear discriminants.

The study focuses on the problems of dimensionality reduction by means of principal component analysis (PCA) in the context of single-trial EEG data classification (i.e. discriminating between imagined left- and right-hand movement). The principal components with the highest variance, however, do not necessarily carry the greatest information to enable a discrimination between classes. An EEG data set is presented where principal components with high variance cannot be used for discrimination. In addition, a method based on linear discriminant analysis (LDA), is introduced that detects principal components which can be used for discrimination, leading to data sets of reduced dimensionality but similar classification accuracy.

Brain Damage, Chronic↗
PubMed1998

A software package for non-invasive, real-time beat-to-beat monitoring of stroke volume, blood pressure, total peripheral resistance and for assessment of autonomic function.

The goal of the present study was to develop and evaluate algorithms for non-invasive, real-time, beat-to-beat monitoring of stroke index (SI), blood pressure (BP) and total peripheral resistance index (TPRI) which has a menu-driven interface, suitable for routine use by unskilled staff. In addition, it was our aim to include a meta-analysis for the evaluation of autonomic function derived from the above haemodynamic data. This includes spectral analysis of heart rate (HR), BP, SI and TPRI and the automatic calculation of baroreceptor reflex sensitivity. Impedance cardiography was used for beat-to-beat SI determination, Finapres corrected by an oscillometric blood pressure measurement (Dinamap) on the upper arm for beat-to-beat BP measurement. We demonstrate noise free recordings during physiological (head up tilt) and pharmacological intervention (alpha 1-, beta 2-adrenoreceptor agonists, insulin induced hypoglycemia). The newly developed software should prove valuable for physiological, pharmacological and clinical studies.

Adult↗
PubMed1998

Post-movement beta oscillations studied with linear estimation.

The application of surface laplacian and linear estimation methods to single trial EEG data was studied. EEG was recorded in 3 subjects during voluntary, self-paced extensions and flexions of the index finger. In each subject a post-movement beta synchronisation was found in specific frequency bands. The surface laplacian estimates were calculated using spherical splines and cortical current distributions were constructed using the linear estimation method. Both methods yield similar results and reveal a maximal event-related synchronisation over the left sensorimotor area approximately 500-750 ms after termination of movement.

Adult↗
PubMed1998

Do changes in coherence always reflect changes in functional coupling?

It is well known that the rhythmic activity within the alpha band in the central area may be composed of two different types of rhythms: (i) the Rolandic mu rhythm, representing the intrinsic activity of the sensorimotor area, and (ii) rhythmic activity believed to be generated within parieto-occipital areas and to extend into central regions through volume conduction (the 'classical alpha rhythm'). In this paper we clearly demonstrate that this second type of rhythmic activity is not due to volume conduction from parieto-occipital areas. We also demonstrate the significant impact of the coexistence of these two types of rhythms on the interpretation of interhemispheric coherence measurements.

Alpha Rhythm↗
PubMed1998

Cardiac response induced by voluntary self-paced finger movement.

Cardiac responses induced by slow and brisk voluntary self-paced index finger movements of the dominant and non-dominant hand were investigated in a group of 12 right-handed subjects. Since subjects synchronised movement and respiration, initiating movement preferably during inspiration, a novel method of evaluating the movement-induced cardiac response was used. This method allows one to distinguish the differential effects on the cardiac response due to movement and respiration. The effect of type of movements (slow vs. brisk) and hand (right vs. left) were analysed. Slow movements induced a monophasic cardiac response, consisting of cardiac deceleration preceding and accompanying movement. Brisk movements induced a biphasic cardiac response, consisting of preparatory deceleration followed by slight post-movement cardiac acceleration. Hand-dominance did not influence the movement-induced cardiac response. The results suggest that neocortical structures involved in planning and execution of voluntary movement impinge upon brainstem cardiovascular nuclei. Vagal cardiac outflow is affected and gives rise to movement-induced changes in cardiac chronotropism.

Adult↗
PubMed1998

Event-related beta synchronization after wrist, finger and thumb movement.

Pre-movement event-related desynchronization (ERD) and post-movement event-related synchronization (ERS) were studied in a group of normal subjects during voluntary thumb, index finger and wrist movement. The band power time courses were computed for the upper alpha band (10-12 Hz) and for two frequency bands in the range of beta (16-20 Hz and 20-24 Hz). While a similar mu ERD was found during motor preparation for the 3 movement tasks, significant differences concerning beta synchronization were observed after movement off set. The contralateral percentage beta increase (ERS) was significantly larger in gross movements of the wrist as compared to index finger and thumb movements, which is discussed under the assumption of a cumulative effect. Summarizing, pre-movement desynchronization seems relatively independent of the forthcoming type of movement, whereas the post-movement beta synchronization might depend on the activated muscle mass.

Adult↗
PubMed1998

Postmovement beta synchronization in patients with Parkinson's disease.

Event-related synchronization (ERS) after self-paced, voluntary brisk movement of the right and left thumb was studied in 17 patients with Parkinson's disease (PD) and 17 age-matched control subjects. All patients were receiving L-DOPA and/or DOPA-agonists. The movement-offset-triggered EEG data were analyzed in the 12- to 16-Hz, 16- to 20-Hz, and 20- to 24-Hz bands for eight time intervals after termination of movement. Significant differences in postmovement beta synchronization were observed in all three frequency bands. As compared with the control group, patients with PD showed a remarkably smaller beta ERS. This was the overall main effect for groups, as well as for interactions concerning side of movement and electrode positions. If beta ERS is a measure of recovery of the primary motor area after movement, our results indicate that this ability is impaired in PD patients.

Aged↗
PubMed1998

On the realization of an analytic high-resolution EEG.

The analytic solution of the harmonic downward continuation of the scalp potential field in an N-shell heterogeneous, but isotropic, spherical volume conductor model has been derived. The objective of this paper was to investigate the realization of a so-called "high-resolution electroencephalogram (EEG)": by enhancing the poor spatial resolution of EEG recordings. To this end, the forward problem for a dipolar source arbitrarily located at the source point Q = Q(rs, phi s, theta s) has been determined in a compact matrix notation. It is possible to transfer the potential field given on the outer surface of a spherically shaped volume conductor to an arbitrary inner surface (e.g., to the cortical surface) under consideration of the electrical and geometrical properties of the model. For the application of the proposed method to real-world problems, the coefficients of the series expansion describing the cortical potential distribution are determined by minimizing the squared curvature of the scalp potential field integrated over the scalp surface. Simulation results for distributed sources show that the proposed method is superior to the surface Laplacian method for interelectrode distances below 2.5 cm.

Electrodes↗
PubMed1998

Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters.

Electroencephalogram (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by, e.g., patients with amyotrophic lateral sclerosis (ALS) to develop a simple binary response in order to reply to specific questions. Four subjects participated in a series of on-line sessions with an EEG-based cursor control. The EEG was recorded from electrodes overlying sensory-motor areas during left and right motor imagery. The EEG signals were analyzed in subject-specific frequency bands and classified on-line by a neural network. The network output was used as a feedback signal. The on-line error (100%-perfect classification) was between 10.0 and 38.1%. In addition, the single-trial data were also analyzed off-line by using an adaptive autoregressive (AAR) model of order 6. With a linear discriminant analysis the estimated parameters for left and right motor imagery were separated. The error rate obtained varied between 5.8 and 32.8% and was, on average, better than the on-line results. By using the AAR-model for on-line classification an improvement in the error rate can be expected, however, with a classification delay around 1 s.

Adult↗
PubMed1998

EEG-based communication: improved accuracy by response verification.

Humans can learn to control the amplitude of electroencephalographic (EEG) activity in specific frequency bands over sensorimotor cortex and use it to move a cursor to a target on a computer screen. EEG-based communication could provide a new augmentative communication channel for individuals with motor disabilities. In the present system, each dimension of cursor movement is controlled by a linear equation. While the intercept in the equation is continually updated, it does not perfectly eliminate the impact of spontaneous variations in EEG amplitude. This imperfection reduces the accuracy of cursor movement. We evaluated a response verification (RV) procedure in which each outcome is determined by two opposite trials (e.g., one top-target trial and one bottom-target trial). Success, or failure, on both is required for a definitive outcome. The RV procedure reduces errors due to imperfection in intercept selection. Accuracy for opposite-trial pairs exceeds that predicted from the accuracies of individual trials, and greatly exceeds that for same-trial pairs. The RV procedure should be particularly valuable when the first trial has >2 possible targets, because the second trial need only confirm or deny the outcome of the first, and it should be applicable to nonlinear as well as to linear algorithms.

Adult↗
PubMed1997

Motor imagery activates primary sensorimotor area in humans.

The spatiotemporal patterns of Rolandic mu and beta rhythms were studied during motor imagery with a dense array of EEG electrodes. The subjects were instructed to imagine movements of either the right or the left hand, corresponding to visual stimuli on a computer screen. It was found that unilateral motor imagery results in a short-lasting and localized EEG change over the primary sensorimotor area. The Rolandic rhythms displayed an event-related desynchronization (ERD) only over the contralateral hemisphere. In two of the three investigated subjects, an enhanced Rolandic rhythm was found over the ipsilateral side. The pattern of EEG desynchronization related to imagination of a movement was similar to the pattern during planning of a voluntary movement.

Adult↗
PubMed1997

On the existence of different alpha band rhythms in the hand area of man.

Earlier investigations have reported that the Rolandic mu rhythm and the parieto-occipital alpha rhythm, the latter thought to be volume-conducted into central areas, both contribute to scalp-recorded electroencephalogram (EEG) in the central region of humans. The present study applies dynamic cross-spectral analysis to event-related EEG data recorded during finger movement. In 10 of 12 subjects, a superposition of Rolandic mu rhythms and bilaterally coherent alpha band rhythms is found in the central area; however, the use of closely-spaced Laplacian derivations rules out volume-conduction effects, providing evidence that both rhythms are generated in the underlying neocortical circuitry. An explanation for the coexistence of these rhythms in terms of a global/local EEG model is provided.

Alpha Rhythm↗
PubMed1997

On the existence of different types of central beta rhythms below 30 Hz.

EEGs were recorded from sensorimotor areas of 12 subjects performing unilateral self-paced brisk and slow finger movements. Two different beta components were found below 30 Hz: (i) One component, at about twice the frequency of the mu rhythm, showed desynchronization in parallel with the mu rhythm starting at about 2 s prior to movement. Measurements of bicoherence have shown that this beta component can be non-linearly related to the arch-shaped mu rhythm. (ii) Another beta component started to desynchronize about 1 s prior to movement, recovered very fast and displayed a pronounced post-movement beta synchronization (PMBS) within the first second after movement-offset. This PMBS was found in the frequency band between 12 and 26 Hz. The average percentage power increase at contralateral sensorimotor area was 232% (SD = 82%) for brisk and 265% (SD = 102%) for slow movements. The PMBS was of contralateral dominance and is interpreted as a correlate of active inhibition or idling of the primary motor area following movement execution.

Beta Rhythm↗
PubMed1997

The effects of external load on movement-related changes of the sensorimotor EEG rhythms.

The effects of external load opposing brisk voluntary extension of the right index finger on the EEG rhythms in the left and right sensorimotor hand area were studied in 13 right-handed subjects. Four levels of external loads corresponding to the weights of 0 g (no load), 30 g, 80 g and 130 g were used. The effects of external load on EEG rhythms were the following: (i) prior to movement, the desynchronisation of beta-rhythms (18-25 Hz) over the contralateral sensorimotor area was greater under the two largest loads as compared to the 0 g load. However, beta-desynchronisation at ipsilateral electrodes was larger under the 80 g load than under the 130 g load, presumably due to a transcallosally mediated inhibition exerted by the highly excited contralateral motor area; (ii) the mu-rhythm desynchronisation continued over both hemispheres for about 0.3-0.4 s after movement and the largest load was accompanied by the longest mu-rhythm desynchronisation; (iii) the post-movement beta-synchronisation was also longer under the heaviest load (130 g) as compared to the no-load condition (0 g), especially in subjects who prolonged their total movement time under the heaviest load. The results show that (i) the movement-related desynchronisation and synchronisation of sensorimotor EEG rhythms is influenced by external load opposing finger movement, and (ii) the effects of external load differ for the mu- and beta-rhythms.

Adult↗
PubMed1997

EEG-based discrimination between imagination of right and left hand movement.

Three subjects were asked to imagine either right or left hand movement depending on a visual cue stimulus. The interval between two consecutive imagination tasks was > 10 s. Each subject imagined a total of 160 hand movements in each of 3-4 sessions (training) without feedback and 7-8 sessions with feedback. The EEG was recorded bipolarly from left and right central and parietal regions and was sampled at 128 Hz. In the feedback sessions, the EEG from both central channels was classified on-line with a neural network classifier, and the success of the discrimination between left and right movement imagination was given within 1.5 s by means of a visual feedback. For each subject, different frequency components in the alpha and beta band were found which provided best discrimination between left and right hand movement imagination. These frequency bands varied between 9 and 14 Hz and between 18 and 26 Hz. The accuracy of on-line classification was approximately 80% in all 3 subjects and did not improve with increasing number of sessions. By averaging over all training and over all feedback sessions, the EEG data revealed a significant desynchronisation (ERD) over the contralateral central area and synchronisation (ERS) over the ipsilateral side. The ERD/ERS patterns over all sessions displayed a relatively small intra-subject variability with slight differences between sessions with and without feedback.

Adult↗