bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptation of the Calcium-dependent Tension Development in Ventricular Cardiomyocytes
Authors: Appel Stephanie , Gerach Tobias , Dössel Olaf , Loewe Axel 
Published: December 2021

Abstract
Today a variety of models describe the physiological behavior of the heart on a cellular level. The intracellular calcium concentration plays an important role, since it is the main driver for the active contraction of the heart. Due to different implementations of the calcium dynamics, simulating cardiac electromechanics can lead to severely different behaviors of the active tension when coupling the same tension model with different electrophysiological models. To handle these variations, we present an optimization tool that adapts the parameters of the most recent, human based tension model. The goal is to generate a physiologically valid tension development when coupled to an electrophysiological cellular model independent of the specifics of that model's calcium transient. In this work, we focus on a ventricular cell model. In order to identify the calcium-sensitive parameters, a sensitivity analysis of the tension model was carried out. In a further step, the cell model was adapted to reproduce the sarcomere length-dependent behavior of troponin C. With a maximum relative deviation of 20.3% per defined characteristic of the tension development, satisfactory results could be obtained for isometric twitch tension. Considering the length-dependent troponin handling, physiological behavior could be reproduced. In conclusion, we propose an algorithm to adapt the tension development model to any calcium transient input to achieve a physiologically valid active contraction on a cellular level. As a proof of concept, the algorithm is successfully applied to one of the most recent human ventricular cell models. This is an important step towards fully coupled electromechanical heart models, which are a valuable tool in personalized health care.
Sensitivity and Generalization of a Neural Network for Estimating Left Atrial Fibrotic Volume Fractions from the 12-lead ECG
Authors: Nagel Claudia , Dössel Olaf , Loewe Axel 
Published: December 2021

Abstract
Features extracted from P waves of the 12-lead electrocardiogram (ECG) have proven valuable for noninvasively estimating the left atrial fibrotic volume fraction associated with the arrhythmogenesis of atrial fibrillation. However, feature extraction in the clinical context is prone to errors and oftentimes yields unreliable results in the presence of noise. This leads to inaccurate input values provided to machine learning algorithms tailored at estimating the amount of atrial fibrosis with clinical ECGs. Another important aspect for clinical translation is the network’s generalization ability regarding new ECGs. To quantify a network’s sensitivity to inaccurately extracted P wave features, we added Gaussian noise to the features extracted from 540,000 simulated ECGs consisting of P wave duration, dispersion, terminal force in lead V1, peak-to-peak amplitudes, and additionally thoracic and atrial volumes. For assessing generalization, we evaluated the network performance for train-validation-test splits divided such that ECGs simulated with the same atria or torso geometry only belonged to either the training and validation or the test set. The root mean squared error (RMSE) of the network increased the most in case of noisy torso volumes and P wave durations. Large generalization errors with a RMSE difference between training and test set of more than 2% fibrotic volume fraction only occurred if very high or low atria and torso volumes were left out during training. Our results suggest that P wave duration and thoracic volume are features that have to be measured accurately if employed for estimating atrial fibrosis with a neural network. Furthermore, our method is capable of generalizing well to ECGs simulated with anatomical models excluded during training and thus meets an important requirement for clinical translation.
Long term EIT based compliance monitoring in COVID-19 patients
Authors: Isasa Reinoso Imanol , Chen Rongqing , Lovas András , Moeller Knut 
Published: December 2021

Abstract
The COVID-19 is a viral infection that causes respiratory complications. Infected lungs often present ground glass opacities, thus suggesting that medical imaging technologies could provide useful information for the disease diagnosis, treatment, and posterior recovery. The Electrical Impedance Tomography (EIT) is a non-invasive, radiationfree, and continuous technology that generates images by using a sequence of current injections and voltage measurements around the body, making it very appropriate for the study to monitor the regional behaviour of the lung. Moreover, this tool could also be used for a preliminary COVID-19 phenotype classification of the patients. This study is based on the monitoring of lung compliances of two COVID-19-infected patients: the results indicate that one of them could belong to the H-type, while the other is speculated belongs to L-type. It has been concluded that the EIT is a useful tool to obtain information regarding COVID-19 patients and could also be used to classify different phenotypes.
Partial 3D-reconstruction of the colon from monoscopic colonoscopy videos using shape-from-motion and deep learning
Authors: Walluscheck Sina , Wittenberg Thomas , Bruns Volker , Eixelberger Thomas , Hackner Ralf 
Published: December 2021

Abstract
For the image-based documentation of a colonoscopy procedure, a 3D-reconstuction of the hollow colon structure from endoscopic video streams is desirable. To obtain this reconstruction, 3D information about the colon has to be extracted from monocular colonoscopy image sequences. This information can be provided by estimating depth through shape-from-motion approaches, using the image information from two successive image frames and the exact knowledge of their disparity. Nevertheless, during a standard colonoscopy the spatial offset between successive frames is continuously changing. Thus, in this work deep convolutional neural networks (DCNNs) are applied in order to obtain piecewise depth maps and point clouds of the colon. These pieces can then be fused for a partial 3D reconstruction.
Biphasic parameter identification of 3D scaffold-free cartilage transplants (SFCT) from stress relaxation compression tests using an optimized 3D FE-based method with tension-compression nonlinearity
Authors: Reuter Thomas , Ponomarev Igor 
Published: December 2021

Abstract
Cartilage constructs produced by SFCTtechnology provide promising opportunities to restore cartilage defects. Mechanical parameters of soft tissues are explicit markers for quantitative tissue characterization. In this study, we present a biphasic 3D-FE-based method to determine the biomechanical properties of SFCT from stress relaxation compression tests (ε = 20 %, t = 3400 s) whereby cartilaginous tissue is modeled as a biphasic material with tension-compression nonlinearity (BMTCN). The FE-model computation was optimized by exploiting the axial symmetry and mesh resolution. The R² of the fit results varies between 0.970 and 0.983. The Young’s and fiber modulus determined from SFCT are 37-times and 5-times lower than from native articular cartilage, respectively. Permeability, on the other hand, is 11-times higher than from native articular cartilage.
Micro injection molding of individualised implants using 3D printed molds manufactured via digital light processing
Authors: Mau Robert , Jüttner Gábor , Gao Ziwen , Matin Farnaz , Alcacer Labrador Dorian , Repp Felix , John Samuel , Scheper Verena , Lenarz Thomas , Seitz Hermann 
Published: December 2021

Abstract
Here, we demonstrate a manufacturing process for individualised, small-sized implant prototypes. Our process is promising for the manufacturing of drug-releasing (micro)implants to be implanted in the round window niche (RWN-I, solid body, free-form-shaped design, 1.1 x 2.7 x 3.1 mm) and for frontal neo-ostium implants (FO-I, tube-like design, length ~ 7 mm, Ø ~ 2-6 mm) for frontal sinus drainage. Implant prototypes are manufactured using micro injection molding (μIM). We use digital light processing (DLP) as a 3D printing technique for rapid tooling of accurate molds for the μIM process. A common acrylate-based photopolymer for stiff and high-detailed modelling but with low head deflection temperature of HDT = 60.5 °C is used for DLP 3D printing of the molds. The molds were 3D printed with a layer height of 50 μm in about 20 min (RWN-I) and 60 min (FO-I). For μIM investigations, we use liquid silicone rubber (LSR) as a biocompatible and medically relevant material. Micro injection molding of LSR was investigated using mold temperatures between Tmold = 110 °C (long tcuring ~ 2 h) up to Tmold = 160 °C (short tcuring ~ 5 min). As a result, small-sized, complex-shaped implant prototypes of LSR can be successfully manufactured via μIM using high Tmold = 160 °C and short curing time. DLP 3D printing material with relative low HDT = 60.5 °C was suitable for μIM. There is no significant wear of the molds, when used for a low number of μIM cycles (n ~ 8). Design of metal mold housing has to be suitable (perfect fit of mold, no cavities facing the molds surface for prevention of thermal expansion of mold into cavities).
Antibiotic-loaded nonwovens as protection against implant-associated infection
Authors: Oschatz Stefan , Illner Sabine , Reske Thomas , Schmitz Klaus-Peter , Woitschach Franziska , Sombetzki Martina , Reisinger Emil C. , Grabow Niels 
Published: December 2021

Abstract
Implant-associated infections still must be considered as a major risk factor and represent a significant threat to the well-being of patients. The detection of such complications is often late, making therapy at this stage difficult. However, the common route of systemic antibiotic prophylaxis can be associated with numerous side effects on the patient or even lead to resistant strains of bacteria. In this context, local antibiotic drug load is a promising way to protect implants against pathogen adhesion and biofilm formation. This work addresses the incorporation of the antibiotic Doxycycline into a biodegradable nonwoven matrix as potential implant coating. While the nonwoven matrix itself displayed already inhibitory effects on Staphylococcus aureus (S. aureus) biofilm formation in vitro, this effect was even more pronounced by the incorporation of Doxycycline. Antibiotic loaded nonwovens display the possibility for local inhibition of biofilm formation. In the shape of an implant coating, this may further help to avoid implantassociated infections. Nevertheless, as pathogens vary in shape and type, further adjustments have to be performed to improve wide-ranging protective effects
Validation of a solvent-based process for the smoothing of additively manufactured 3D models of nasal cavities
Authors: Meile Viktor , Tymkovych Maksym , Rusiecki Tobias , Nosova Yana , Pape Florian , Poll Gerhard , Glasmacher Birgit , Avrunin Oleg , Gryshkov Oleksandr 
Published: December 2021

Abstract
In order to improve the reliability of diagnosis of nasal breathing disorders, aerodynamic properties have to be analyzed through experiments based on 3D models. The surface properties of the prepared respective 3D models using fused deposition modeling (FDM) should match those of native nasal cavities, thus representing their normal state and typical pathologies. In this work, we validated the smoothing of dual extruded 3D printed samples of PLA (polylactide) and PVA (polyvinyl alcohol) using the solvent TFE (trifluoroethanol). The smoothing was conducted in vapour and liquid phases of TFE. Before and after treatment of the samples in liquid and vapour phases of TFE, mass and surface roughness analysis were performed. The results of this work will help to produce and process a representative model of the human paranasal sinuses, which can be created using CT data from a patient.
Passive Acoustic Mapping for ultrasound therapy monitoring
Authors: Therre Sarah , Bost Wolfgang , Hewener Holger , Tretbar Steffen , Fournelle Marc 
Published: December 2021

Abstract
Passive Acoustic Mapping (PAM) is an ultrasoundbased imaging method developed for monitoring therapeutic ultrasound. By using diagnostic transducers to passively record the acoustic signals that are emitted by cavitation bubbles, the origin of the bubbles can be reconstructed and displayed as intensity maps. In this study, two matrix arrays with different aperture sizes were used for the volumetric reconstruction of simulated and experimental data. In a second step, the number of elements being used for the reconstruction was reduced by more than the factor of eight in order to assess the influence on the imaging quality. In the numerical part of the study, the image quality was greatly improved by increasing the aperture size, while a high number of elements used for the reconstruction merely offers minor improvements. The experimentally obtained results were able to confirm the numerical findings regarding the achievable reconstruction quality.
Laser-Guided CT Intervention using Flexible Laser Bow
Authors: Jain Hardik , Hellwich Olaf , Wotke Nils , Szymanski Daniel , Rose Andreas , Krüger Timo 
Published: December 2021

Abstract
Laser bow systems are used for intervention guidance by steering laser rays. Such systems have shown applications in biopsy, nasal surgeries, drainage, pain therapy. In this paper, we introduce an image-based laser guided CT intervention. Instead of relying on traditional laser bow rigidly mounted to the CT scanner, our approach performs registration making use of a patient tracker in image as well as CT data to find the orientation of laser bow with respect to the CT data. The image is acquired by a camera rigidly connected to the laser bow. The proposed approach allows movability to the laser bow system without compromising on accuracy. Using camera allows real-time view of the intervention and can be used for futuristic applications.
Scaffolds with Magnetic Nanoparticles for Tissue Stimulation
Authors: Leal-Marin Sara , Gallaway Glynn , Höltje Kai , Lopera-Sepulveda Alex , Glasmacher Birgit , Gryshkov Oleksandr 
Published: December 2021

Abstract
Magnetic nanoparticles (MNPs) have been used in several medical applications, including targeted hyperthermia, resonance tomography, diagnostic sensors, and localized drug delivery. Further applications of magnetic field manipulation through MNPs in tissue engineering have been described. The current study aims to develop tissue-engineered polymeric scaffolds with incorporated MNPs for applications that require stimulation of the tissues such as nerves, muscles, or heart. Electrospun scaffolds were obtained using 14%w/v polycaprolactone (PCL) in 2,2,2-Trifluoroethanol (TFE) at concentrations of 5% & 7.5%w/v of dispersed MNPs (iron oxide, Fe3O4, or cobalt iron oxide, CoFe2O4). Scaffolds were analyzed using scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy, uniaxial tensile testing, and cell seeding for biocompatibility. Human bone marrow mesenchymal stem cells (bmMSCs) were seeded on the scaffolds. Biocompatibility was assessed by metabolic activity with Resazurin reduction assay on day 1, 3, 7, 10. Cell-cell and cell-scaffold interactions were analyzed by SEM. Electrospun scaffolds containing MNPs showed a decrease in fiber diameter as compared to scaffolds of pure PCL. The maximum force increases with the inclusion of MNPs, with higher values revealed for iron oxide. The metabolic activity decreased with MNPs, especially for cobalt iron oxide at a higher concentration. On the other hand, the cells developed good cell-scaffold and cell-cell interactions, making the proposed scaffolds good prospects for potential use in tissue stimulation.
Evaluation of an algorithm for optical pulse detection in children for application to the Pepper robot
Authors: Lang Nadine , Goes N. , Struck M. , Wittenberg T. , Goes N. , Seßner J. , Franke J. , Wittenberg T. , Dziobek I. , Kirst S. , Naumann S. 
Published: December 2021

Abstract
To engage in socio-emotional interactions, children with autism spectrum conditions (ASC) need support to understand and convey emotions. In our approach, a humanoid robot (Pepper, Softbanks Robotics) acts as a tutor for the child within autism care. The robot, equipped with multimodal sensor technology to acquire the emotional feedback of the child, stimulates the child to perform tasks, adapted to its current arousal state. By in-, or decreasing the difficulties of implemented training modules, the child can be given the appropriate task according to its emotional state. The child’s arousal is measured with different techniques implemented in and on the robot: emotion detection based on audio recordings of the speech signal and camera detected facial expressions, or heart rate. To this end, the remote Photoplethysmography (rPPG) signal from camera recordings of the subjects’ face is acquired. While its unintrusive measurement is an advantage, a major drawback for rPPG is its proneness to motion and light artefacts requiring de-noising steps. A wavelet transform based on log-Gabor wavelets and a filter bank with 32 filters was implemented. The signal was filtered with a prior filter and afterwards with a Markov chain in order to extract the underlying pulse rate. Within an initial study, five children were observed watching videos with different co-notated emotions. As reference for the heart rate (HR), a wristband (empatica E4) was used. The captured emotions of all subjects were annotated to identify low and high arousal parts and positive and negative emotions. Extracted HR from rPPG-data indicated a correlation with the annotated emotions.
Ultrathin fibre coatings on nanofibrous nonwovens by plasma enhanced chemical vapor deposition
Authors: Teske Michael , Illner Sabine , Markhoff Jana , Grabow Niels , Oschatz Stefan 
Published: December 2021

Abstract
For the generation of tailor-made polymer coatings on nanofibrous nonwovens plasma enhanced chemical vapor (PECVD) is a promising process, even for complex geometries. The plasma coatings can greatly improve their suitability for biomedical applications by optimising biocompatibility to the local needs, especially for cardiovascular disease treatments. Therein, wound healing and endothelialisation are important steps which are connected by a complex interaction. The monomers allylamine and hexamethyldisiloxane, as well as different process conditions were studied for the coating of nanofibrous thermoplastic silicone polycarbonate polyurethane (TSPCU) nonwovens. Aim of this study was to investigate the feasibility of plasma polymer coating under preservation of the nanofibrous morphological structure. Beside characterization of the nonwoven, biological evaluation with endothelial and fibroblast cells was performed. The prepared nonwoven samples support the feasibility of plasma coating under preservation of the nanofibrous structure. Also, different effects of the surfaces in contact with fibroblasts and endothelial cells could be observed.
Optimization and evaluation of motion sequences of an averaged human motion model by using kinematic techniques and new evaluation methods
Authors: Kitzig Andreas , Demmer Julia , Naroska Edwin , Stockmanns Gudrun , Viga Reinhard , Grabmaier Anton 
Published: December 2021

Abstract
Signal processing, pattern recognition as well as modelling and simulation require a large amount of reference data, both for the development of new methods and for their evaluation. Depending on the application, the availability of databases is rather low. In the field of biosignal processing with a focus on the functionalization of furniture for nursing and hospital facilities, a database from a motion capturing system (MoCap), and a method to generate averaged human motion sequences was presented in subsequent works by our research group. Evaluations revealed that the averaged motion sequences partly contain artifacts caused by the averaging and thus are not directly usable. To use the averaged motion sequences e.g., in simulation tasks, this paper presents an extension with kinematic methods to combine averaged motion sequences and to suppress and thus optimize inappropriate motion artifacts by error correction. To check whether the results are usable after the processing steps, four evaluation criteria are proposed. The evaluation of the resulting motion sequences shows that sequences are generated which do not fully correspond to human motion sequences but are well suited for simulation tasks.
Optimal Sensor Location in a Smart-Shirt to Measure Accurate Tidal Volumes During Abdominal and Thoracic Respiration
Authors: Laufer Bernhard , Docherty Paul D. , Murray Rua , Jalal Nour Aldeen , Hoeflinger Fabian , Reindl Leonhard , Moeller Knut 
Published: December 2021

Abstract
The determination of respiratory parameters via respiration induced surface movements of the upper body has been the subject of research for many years. The displacements of 102 motion capture markers were evaluated in this study in terms of their information content with respect to the tidal volume recorded in parallel using a spirometer. Independent of the breathing types (spontaneous breathing, abdominal breathing, or chest breathing), the number and the location of sensors in a smart shirt to obtain tidal volume information was determined. Only 9 of 102 sensors were sufficient to obtain breathing volume information.
Comparison of a histology based multi layer artery model to its simplified axisymmetric model.
Authors: Bhave Ashish , Möller Knut 
Published: December 2021

Abstract
Arteries are vessel structures that serve vital function of transportation of blood to different parts of the body. Researchers have experimented with some approaches to model the arterial behaviour and to analyse its biomechanical properties. To analyse the in-vivo arterial properties, at Furtwangen University an inflatable sensoractuator system is being developed, which provides the basis for a decision support system for vascular surgeons. The capabilities of this sensor shall be evaluated in simulations which requires appropriate modelling of the arteries. The inverse problem, i.e. how to efficiently identify arterial wall properties from sensor readings is targeted. A histology motivated 3D artery model was implemented in FEM using COMSOL (v5.5). The geometry of one model was based on a cross section of a real artery. The second model was axisymmetric and of equal dimensions with respect to volume, layer thickness etc. A biomechanical pressure-stretch analysis was performed applying an inflating pressure inside the walls of the vessels. Stretch in different areas of the first model was evaluated and the circumferential strain was compared to the axisymmetric model. The results show variation of strains within the segments of the first model of upto 10 percent. In addition, its outer wall circumferential stretch was found to be 10 percent lower compared to the axisymmetric setup. This comparison sheds light upon whether a simplification of arterial models is possible, without loss of accuracy in the context of the novel sensor evaluation. It provides useful information whether e.g. standardizing vessel structures to axisymmetric models will still provide results within allowable tolerance limits. Simulations proved useful to evaluate different vessel model formulations in the context of arterial diagnostics.