IOS Press
Refine
Institute
- Fachbereich Chemie und Biotechnologie (1)
- Fachbereich Elektrotechnik und Informationstechnik (1)
- Fachbereich Maschinenbau und Mechatronik (1)
- Fachbereich Medizintechnik und Technomathematik (1)
- IaAM - Institut für angewandte Automation und Mechatronik (1)
- IfB - Institut für Bioengineering (1)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (1)
Has Fulltext
- no (4)
Language
- English (4)
Document Type
- Article (2)
- Part of a Book (1)
- Conference Proceeding (1)
Keywords
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
BACKGROUND: Muscle stretch reflexes are widely used to examine neural muscle function. The knowledge of reflex response in muscles crossing the shoulder is limited. OBJECTIVE: To quantify reflex modulation according to various subject postures and different procedures of muscle pre-activation steering. METHODS: Thirteen healthy male participants performed two sets of external shoulder rotation stretches in various positions and with different procedures of muscle pre-activation steering on an isokinetic dynamometer over a range of two different pre-activation levels. All stretches were applied with a dynamometer acceleration of 104∘/s2 and a velocity of 150∘/s. Electromyographical response was measured via sEMG. RESULTS: Consistent reflexive response was observed in all tested muscles in all experimental conditions. The reflex elicitation rate revealed a significant muscle main effect (F (5,288) = 2.358, ρ= 0.040; η2= 0.039; f= 0.637) and a significant test condition main effect (F (1,288) = 5.884, ρ= 0.016; η2= 0.020; f= 0.143). Reflex latency revealed a significant muscle pre-activation level main effect (F (1,274) = 5.008, ρ= 0.026; η2= 0.018; f= 0.469). CONCLUSION: Muscular reflexive response was more consistent in the primary internal rotators of the shoulder. Supine posture in combination with visual feedback of muscle pre-activation level enhanced the reflex elicitation rate.
Comparison of intravenous immunoglobulins for naturally occurring autoantibodies against amyloid-β
(2010)
Intravenous immunoglobulins (IVIG) are currently used for therapeutic purposes in autoimmune disorders. Recently, we demonstrated the presence of naturally occurring antibodies against amyloid- β (nAbs-Aβ) within the pool of IVIG. In this study, we compared different brands of IVIG for nAbs-Aβ and have found differences in the specificity of the nAbs-Aβ towards Aβ1–40 and Aβ1–42 . We analyzed the influence of a pH-shift over the course of antibody storage using ELISA and investigated antibody dimerization at acidic and neutral pH as well as differences in the IgG subclass distributions among the IVIG using both HPLC and a nephelometric assay. Furthermore, we investigated the epitope region of purified nAbs-Aβ. The differences found in Aβ specificity are not directly proportionate to the binding nature of these antibodies when administered in vivo. This information, however, may serve as a guide when choosing the commercial source of IVIG for therapeutic applications in Alzheimer's disease
