Tilmann Heinrich Sander

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BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology,(More)
Functional magnetic resonance imaging (fMRI) visualizes activated brain areas with a high spatial resolution. The activation signal is determined by the local change of cerebral blood oxygenation, blood volume and blood flow which serve as surrogate marker for the neuronal signal itself. Here, the complex coupling between these parameters and the(More)
The 170-ms electrophysiological processing stage (N170 in EEG, M170 in MEG) is considered an important computational step in face processing. Hence its neuronal sources have been modelled in several studies. The current study aimed to specify the relation of the dipolar sources underlying N170 and M170. Whole head EEG and MEG were measured simultaneously(More)
To reduce physiological artifacts in magnetoencephalographic (MEG) and electroencephalographic recordings, a number of methods have been applied in the past such as principal component analysis, signal-space projection, regression using secondary information, and independent component analysis. This method has become popular as it does not have constraints(More)
We report on the measurement of somatosensory-evoked and spontaneous magnetoencephalography (MEG) signals with a chip-scale atomic magnetometer (CSAM) based on optical spectroscopy of alkali atoms. The uncooled, fiber-coupled CSAM has a sensitive volume of 0.77 mm(3) inside a sensor head of volume 1 cm(3) and enabled convenient handling, similar to an(More)
First, the intrinsic random noise sources of a biopotential measurement in general are reviewed. For the special case of an electroencephalographic (EEG) measurement we have extended the commonly used amplifier noise model by biological generated background noise. As the strongest of all noise sources involved will dominate the resulting signal to noise(More)
Determining the centers of electrical activity in the human body and the connectivity between different centers of activity in the brain is an active area of research. To understand brain function and the nature of cardiovascular diseases requires sophisticated methods applicable to non-invasively measured bioelectric and biomagnetic data. As it is(More)
The temporal relation between vascular and neuronal responses of the brain to external stimuli is not precisely known. For a better understanding of the neuro-vascular coupling changes in cerebral blood volume and oxygenation have to be measured simultaneously with neuronal currents. With this motivation modulation dc-magnetoencephalography was combined(More)
In a pilot study, stroke patients with a lesion related to the motor system were studied using magnetoencephalography (MEG) and electromyography (EMG). The patients performed sustained finger movements for 30 s followed by 30 s of rest and 20 repetitions of this sequence in total. Task-related cortical signals derived from MEG were observed here at very(More)