Showing papers by "Gernot Müller-Putz published in 2005"

Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components

Abstract: Brain-computer interfaces (BCIs) can be realized on the basis of steady-state evoked potentials (SSEPs). These types of brain signals resulting from repetitive stimulation have the same fundamental frequency as the stimulation but also include higher harmonics. This study investigated how the classification accuracy of a 4-class BCI system can be improved by incorporating visually evoked harmonic oscillations. The current study revealed that the use of three SSVEP harmonics yielded a significantly higher classification accuracy than was the case for one or two harmonics. During feedback experiments, the five subjects investigated reached a classification accuracy between 42.5% and 94.4%.

EEG-based asynchronous BCI controls functional electrical stimulation in a tetraplegic patient

Abstract: The present study reports on the use of an EEG-based asynchronous (uncued, user-driven) brain-computer interface (BCI) for the control of functional electrical stimulation (FES). By the application of FES, noninvasive restoration of hand grasp function in a tetraplegic patient was achieved. The patient was able to induce bursts of beta oscillations by imagination of foot movement. These beta oscillations were recorded in a one EEG-channel configuration, bandpass filtered and squared. When this beta activity exceeded a predefined threshold, a trigger for the FES was generated. Whenever the trigger was detected, a subsequent switching of a grasp sequence composed of 4 phases occurred. The patient was able to grasp a glass with the paralyzed hand completely on his own without additional help or other technical aids.

Synchronous occurrence of EEG bursts and heart rate acceleration in preterm infants.

Abstract: Continuous and simultaneous registration of electroencephalogram (EEG) and heart rate (HR) pattern in preterm infants can give information about the functioning of central nervous system and the integrity of the autonomic nervous system. The developmental and behavioural state determine the pattern of EEG activity. A discontinuous EEG activity also known as ‘Trace alternant’ (TA) in preterm infants is accompanied by a low heart rate variability (HRV). It was found that electroencephalographic bursts of slow waves during TA are coupled with an acceleration of the HR. In this study, this synchronous behaviour of EEG bursts and HR is described for the first time in a group of preterm infants with a mean conceptional age (CA) of 36 weeks.

[Semiautomatic procedure for the investigation of synchronized activity of EEG and heart rate--examination of preterm births].

Abstract: Recordings of the electroencephalogram (EEG) and of the heart rate variability (HRV) of preterm neonates can give important information on the actual state of the nervous system. Both signals, EEG and HRV, are affected by parameters such as gestational age, stage of maturation and behavioral state. This work describes a method for automatic detection of slow wave EEG-bursts and a tool to average changes in the EEG and the corresponding heart rate. The detection is based on the hjorth activity (HA), calculated from the EEG. HA spikes (HAS) are identified by the determination of the beginning and end of existing spikes. HAS maxima and the time between two consecutive HAS are the basis for the triggering of the bursts. EEG power and time synchronized HR changes are averaged with a time window length of 20 s. Resultant, HR increase and duration are determined. These parameters, obtained by the automatic detection, proved to be comparable to the results of an expert.