FG Elektronik und medizinische Signalverarbeitung

10 Items

Recent Submissions
Enabling continuous blood pressure estimation on artifact contaminated recordings applying a novel pulse wave signal quality detector

Pflugradt, Maik (2018)

The universe of home-monitoring and unobtrusive longtime measurements has experienced a remarkable development in the past years. Smart and cheap recording devices interconnected to body sensor networks have emerged in a great variety, promoting features such as on-line signal processing, low power consumption and high data rates. These hardware systems provide a novel platform for ambitious me...

Recent advances in modeling and analysis of bioelectric and biomagnetic sources

Sander, Tilmann H. ; Knösche, Thomas R. ; Schlögl, Alois ; Kohl, Florian ; Wolters, Carsten H. ; Haueisen, Jens ; Trahms, Lutz (2010)

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 difficult to solve for all unknown parameters ...

A novel method for motion artifact removal in wearable ppg sensors based on blind source separation

Pflugradt, Maik ; Rose, Marcus ; Orglmeister, Reinhold (2013)

The recent development of healthcare systems has provided a significant contribution to ambulatory patient monitoring. In that context, signal quality and disturbances induced by noise or motion artifacts play an important role in the field of signal processing tasks. Especially the Photoplethysmogram (PPG) is very liable to movement artifacts which severely hamper the extraction of vital param...

Automatic validation and quality based readjustment of manually scored EEG arousal

Lerch, Dennis ; Penzel, Thomas ; Orglmeister, Reinhold (2013)

A knowledge of arousals during sleep is important to attain a deeper understanding regarding cardiovascular diseases. Manual scoring is time consuming and not always accurate. Automatic approaches are even worse inter alia due to inaccurate learning data. This paper presents an algorithm to improve the accuracy of manually scored data. Also a measure of quality is introduced to judge the automa...

Computationally efficient time domain detection algorithm for characteristic points in non invasive continuous blood pressure measurements

Lerch, Dennis ; Orglmeister, Rreinhold (2012)

In this paper a computationally efficient algorithm for continuous blood pressure curve segmentation is presented. It uses only methods in the time domain and can distinguish between systolic, diastolic values and values of calibration steps caused by the continuous blood pressure measuring technique or values of other artefacts. The detection of local extremes, necessary for systolic and diast...

Automatic analysis of systolic, diastolic and mean blood pressure of continuous measurement before, during and after sleep arousals in polysomnographic overnight recordings

Lerch, Dennis ; Orglmeister, Reinhold ; Penzel, Thomas (2012)

This paper deals with a detailed examination of sleep arousal events and the corresponding changes of systolic, diastolic and mean blood pressure. Arousals are short awakening events during sleep which do not become noticeable for the sleeping person. But the organism increases vital parameters, e.g. the blood pressure. The recreative sleep is disturbed, and the risk factor for cardiovascular d...

ECG, PPG and ABP sensor fusion for a PCA-based respiratory activity estimation

Mann, Steffen ; Orglmeister, Reinhold (2012)


On-line learning algorithms for extracting respiratory activity from single lead ECGs based on principal component analysis

Pflugradt, Maik ; Mann, Steffen ; Feller, Viktor ; Orglmeister, Reinhold (2012)

In this paper we present several statistic gradient algorithms from literature to solve the Principal Component Analysis (PCA) problem. We used a linear artificial neural network forming the basis of the implemented algorithms which is a neat way for on-line computation of the PCA expansion. As convergence is a key-aspect of these algorithms and is cru-cial for the usefulness in particular appl...

Online learning algorithms for principal component analysis applied on single-lead ECGs

Pflugradt, Maik ; Mann, Steffen ; Feller, Viktor ; Lu, Yirong ; Orglmeister, Reinhold (2013)

This article evaluates several adaptive approaches to solve the principal component analysis (PCA) problem applied on single-lead ECGs. Recent studies have shown that the principal components can indicate morphologically or environmentally induced changes in the ECG signal and can be used to extract other vital information such as respiratory activity. Special interest is focused on the converg...

A fast multimodal ectopic beat detection method applied for blood pressure estimation based on pulse wave velocity measurements in wearable sensors

Pflugradt, Maik ; Geißdörfer, Kai ; Görnig, Matthias ; Orglmeister, Reinhold (2017-01-14)

Automatic detection of ectopic beats has become a thoroughly researched topic, with literature providing manifold proposals typically incorporating morphological analysis of the electrocardiogram (ECG). Although being well understood, its utilization is often neglected, especially in practical monitoring situations like online evaluation of signals acquired in wearable sensors. Continuous blood...