Wilhelm von Rosenberg

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Precise detection of R-peaks is a prerequisite in real-world ECG applications - this is particularly critical for wearable ECG where sensors are typically low resolution and embedded. Such recorded ECG data are typically contaminated by noise, motion artefacts, unbalanced skin-electrode impedance and other physiological signals. These affect the quality of(More)
It is essential to measure physiological parameters such as heart rate variability and respiratory rate of drivers to evaluate their performance. The results from this measurement can be used to assess the state of body and mind, for instance concentration and stress. However, current systems only work in controlled environments, or sensors obstruct and(More)
The Electrocardiogram (ECG) collected in real-life scenarios is often noisy and contaminated with motion artefacts. This study proposes a new framework to analyse the heart rate variability (HRV) in mobile scenarios by introducing novel R-peak detection and HRV detrending algorithms. The R-peak detection combines matched filtering and Hilbert transform,(More)
The timing of the assessment of the injuries following a road-traffic accident involving motorcyclists is absolutely crucial, particularly in the events with head trauma. Standard apparatus for monitoring cardiac activity is usually attached to the limbs or the torso, while the brain function is routinely measured with a separate unit connected to the(More)
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