SQUID measurements of human nerve and muscle near-DC injury-currents using a mechanical modulation of the source position

| We apply a recently developed multi-variate statistical data analysis technique - so called blind source separation by independent component analysis - to process MEG recordings of near-DC fields. The extraction of nearDC fields from MEG recordings has great relevance for medical applications since slowly varying DC-phenomena have been found e.g. in cerebral anoxia and spreading depression in animals. Comparing several blind source separation approaches, it turns out that an algorithm based on temporal decorrelation successfully extracted a DC-component which was induced in the auditory cortex by presentation of music. The task is challenging because of the limited amount of available data and the corruption by outliers, which makes it an interesting real-world testbed for studying the robustness of ICA methods. Keywords| Biomagnetism, biomedical data processing, blind source separation, DC-recordings, independent component analysis, magnetoencephalography (MEG). I. Introduction Rec..