Biomedical subjects

B Graimann

Publications and source records attributed to B Graimann.

4 recordsLinked to original sources

PubMed2003

Spatiotemporal patterns of beta desynchronization and gamma synchronization in corticographic data during self-paced movement.

OBJECTIVE: To study the spatiotemporal pattern of event-related desynchronization (ERD) and event-related synchronization (ERS) in electrocorticographic (ECoG) data with closely spaced electrodes. METHODS: Four patients with epilepsy performed self-paced hand movements. The ERD/ERS was quantified and displayed in the form of time-frequency maps. RESULTS: In all subjects, a significant beta ERD with embedded gamma ERS was found. CONCLUSIONS: Self-paced movement is accompanied not only by a relatively widespread mu and beta ERD, but also by a more focused gamma ERS in the 60-90 Hz frequency band.

Adult↗

PubMed2003

Graz-BCI: state of the art and clinical applications.

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.

Amyotrophic Lateral Sclerosis↗

PubMed2002

Visualization of significant ERD/ERS patterns in multichannel EEG and ECoG data.

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.

Algorithms↗

PubMedDate not supplied

Frequency component selection for an ECoG-based brain-computer interface.

The aim of the present study was to investigate the most significant frequency components in electrocorticogram (ECoG) recordings in order to operate a brain computer interface (BCI). For this purpose the time-frequency ERD/ERS map and the distinction sensitive learning vector quantization (DSLVQ) are applied to ECoG from three subjects, recorded during a self-paced finger movement. The results show that the ERD/ERS pattern found in ECoG generally matches the ERD/ERS pattern found in EEG recordings, but has an increased prevalence of frequency components in the beta range.

Brain Mapping↗