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Human health is important for people in any age. Healthcare addresses a market of more than 10% of the European gross domestic product. An ageing population will have an enormous impact on society and the economy. The objective of this article is to provide a view of some latest research innovations in field of bioelectronics. Among these a short description of non-invasive hydration sensor, glucose...
Power supply of intelligent implants, as for example, an intraocular pressure sensor, cannot be handled with conventional voltage sources due to their limited durability. Energy harvesting on the contrary could be a conceivable solution to this task converting mechanical energy of fast eye movements into electrical energy. In this contribution, we investigate the upper limit on the amount of electrical...
To identify the scalp projections of the underlying sources of neural activity based on recorded electroencephalographic (EEG) signals, the multi-dimensional decomposition models Parallel Factor Analysis (PARAFAC) and Parallel Factor Analysis 2 (PARAFAC2) have recently attained interest. We evaluate the models based on synthetic EEG data, because this allows an objective assessment by comparing the...
The higher-order tensor analysis of multi-channel signals and systems has developed to one of the key signal processing areas over the past few years. In this contribution we present a new algorithm for the Parallel Factor (PARAFAC) analysis of tensors obeying a special kind of symmetry, which we refer to as dual-symmetry. This iterative algorithm is based on alternating Procrustes estimation and...
Material transfer in a low-power direct-current switchgear is commonly known to cause contact failures to open due to mechanical interlocking, which is determined by (i) the shape of the material transfer pip-and-crater formation and (ii) the relative movement of the contact pieces during contact separation. The aim of this work is to analyze the influence of multiple arcing parameters on the evolving...
R-dimensional parameter estimation problems are common in a variety of signal processing applications. In order to solve such problems, we propose a robust multidimensional model order selection scheme and a robust multidimensional parameter estimation scheme using the closed-form PARAFAC algorithm, which is a recently proposed way to compute the PARAFAC decomposition based on several simultaneous...
The identification of signal components in electroencephalographic (EEG) data originating from neural activities is a long standing problem in neuroscience. This area has regained new attention due to the possibilities of multi-dimensional signal processing. In this work we analyze measured visual-evoked potentials on the basis of the time-varying spectrum for each channel. Recently, parallel factor...
The identification of signal components in electroencephalographic (EEG) data is a major task in neuroscience. The interest to this area has regained new interest due to the possibilities of multidimensional signal processing. In this contribution we analyze event-related multi-channel EEG recordings on the basis of the time-varying spectrum for each channel. To identify the signal components it is...
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