bluuebunny/crossref_metadata_2025 huggingface dataset:
An automate pipeline for generating fiber orientation and region annotation in patient specific atrial models
Authors: Zheng Tianbao , Azzolin Luca , Sánchez Jorge , Dössel Olaf , Loewe Axel
Published: December 2021

Modeling the 'digital twin' of a patient's heart has gained traction in the last years and helps to understand the pathogenic mechanisms of cardiovascular disease to pave the way for personalized therapies. Although a 3D patient-specific model (PSM) can be obtained from computed tomography (CT) or magnetic resonance imaging (MRI), the fiber orientation of cardiac muscle, which significantly affects the electrophysiological and mechanical characteristics of the heart, can hardly be obtained in vivo. Several approaches have been suggested to solve this problem. However, most of them require a considerable amount of human interaction, which is both time-consuming and a potential source of error. In this work, a highly automated pipeline based on a Laplace- Dirichlet-rule-based method (LDRBM) for annotating fibers and anatomical regions in both atria is introduced. The calculated fiber arrangement was regionally compared with anatomical observations from literature and faithfully reproduced clinical and experimental data.
Spatial Sensitivity of ECG Electrode Placement
Authors: Oltmann Andra , Kusche Roman , Rostalski Philipp
Published: December 2021

The electrocardiogram (ECG) is a well-known technique used to diagnose cardiac diseases. To acquire the spatial signal characteristics from the thorax, multiple electrodes are commonly used. Displacements of electrodes affect the signal morphologies and can lead to incorrect diagnoses. For quantitative analysis of these effects we propose the usage of a numerical computer simulation. In order to create a realistic representation of the human thorax including the heart and lung a three-dimensional model with a simplified geometry is used. The electrical excitation of the heart is modelled on a cellular level via the bidomain approach. To numerically solve the differential equations, describing the signal propagation within the body, we use the finite element method in COMSOL Multiphysics®. The spatial gradients of the simulated body potentials are calculated to determine placement sensitivity maps. The simulated results show that the sensitivity is different for each considered point in time of each ECG wave. In general, the impact of displacement is increased as an electrode is more closely located to the signal source. However, in some specific regions associated with differential ECG leads the placement sensitivity distribution deviates from this simple circular pattern. The results provide useful information to enhance the understanding of placed specific effects on classical ECG features. By additional consideration of patient-specific characteristics in the future, the used model has the ability to investigate additional body-related aspects such as geometrical body shape or composition of various tissue types.
Influence of electric field orientation on the effect of ocular current stimulation using full field electroretinogram
Authors: Blum Maren-Christina , Leydolph Lilly , Klee Sascha
Published: December 2021

Ocular current stimulation (CS) exhibits potential for the treatment of neurodegenerative ocular diseases. For a full field electroretinogram (ffERG) we found no CS effect on the characteristic waves (a-wave, b’-wave, and b-wave). To investigate whether the orientation of the generated electric field has an influence on the CS effect, this study repeated the previous ffERG study with changing one CS electrode position and compared the results of both studies. In the first study 15 (8 m, 27.5 ± 4.5 years) and in the second study 17 (7 m, 22.0 ± 1.9 years) healthy volunteers were stimulated with an anodal, cathodal, and sham direct CS of 800 μA for 5 min in three sessions (randomized, different days). For both studies, a cut-sized ring rubber electrode was placed around the eye. A square rubber electrode was placed for the first study at the ipsilateral temple and for the second study at the visual cortex. Before (ERG 1) and during (ERG 2) the CS, the ffERG was measured. For both studies, the difference between the ERG 1 and ERG 2 measurement (CS effect) for the three characteristic waves was analyzed and compared between the studies. For statistical analysis, the Mann-Whitney U test with Bonferroni correction was applied (α = 0.05). The comparison of the data distribution showed only slight differences between the studies. The Mann-Whitney U test found no significant difference of the CS effect between the studies for all amplitudes and CS groups (p ≥ 0.0055). In the mean, the latency differences were smaller than the time resolution, therefore no statements for latency effects were possible. It can be concluded that the retinal cells generating the ffERG are not affected by ocular CS in either electrode montages tested.
Finding the curved pathway of the large intestine for robot-aided colonoscopy
Authors: Giacoppo Giuliano A. , Mammel Rebecca , Pott Peter P.
Published: December 2021

To assist the insertion of a robot-aided endoscope during colonoscopy, a measuring system is required so that the endoscope tip can align automatically and thus find the curved pathway of the large intestine. To achieve this, a selfexpanding nitinol wire basket is used to sense the contour of the intestine. As the wire basket touches the wall, it is deflected towards the center of the intestine. The relative position of the wire basket within the camera image is captured, which describes the desired direction to follow the organ. To identify the wire basket in the image, the original RGB image stream is converted into the HSV (hue, saturation, value) color space. Thus, a binary image can be created, in which only the neongreen color portion of the wire basket is visible as a cross. The Hough Transformation is used to search for straight lines in the binary image. Once two lines are found, the intersection point can be calculated and thus its position in the image. The evaluation of the execution time of the algorithm on a live stream was 45 ± 31 ms on average. The algorithm robustly recognizes the wire basket even if it was not visible to the human eye in the original RGB image due to deficient lighting.
Image processing-based mTICI grading after endovascular treatment for acute ischemic stroke
Authors: Sabieleish Muhannad , Thormann Maximilian , Metzler Jonathan , Boese Axel , Friebe Michael , Mpotsaris Anastasios , Behme Daniel
Published: December 2021

Abstract Introduction

: The grade of reperfusion after endovascular treatment of ischemic stroke e.g. mechanical thrombectomy is determined based on the mTICI score. The mTICI score shows significant interrater variability; it is usually biased towards better reperfusion results if selfassessed by the operator. We therefore developed a semiautomated image processing technique for assessing and evaluating the degree of reperfusion independently, resulting in a more objective mTICI score. Methods: Fifty angiography datasets of patients who were treated with mechanical thrombectomy for middle cerebral artery (MCA) occlusion were selected from our database. Image datasets were standardized by adjustment of field of view and orientation. Based on pixel intensity features, the internal carotid artery (ICA) curve was detected automatically and used as a starting point for identifying the target downstream territory (TDT) of the MCA on the DSA series. Furthermore, a grid with predefined dimensions was used to divide the TDT into checkzones and be classified as perfused or unperfused. Results: The algorithm detected the TDT and classified each zone of the grid as perfused or unperfused. Lastly, the percentage of the perfused area in the TDT was calculated for each patient and compared to the grading of experienced clinical users. Conclusion: A semi-automatic image-processing workflow was developed to evaluate perfusion rate based on angiographic images. The approach can be used for the objective calculation of the mTICI score. The semi-automatic grading is currently feasible for MCA occlusion but can be extended for other brain territories. The work shows a starting point for a machine learning approach to achieve a fully automated system that can evaluate and give an accurate mTICI score to become a common AI-based grading standard in the coming near future.
Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images
Authors: Abuzer Amr , Naber Ady , Hoffmann Simon , Kessler Lucy , Khoramnia Ramin , Nahm Werner
Published: December 2021

Optical Coherence Tomography Angiography (OCTA) is an imaging modality that provides threedimensional information of the retinal microvasculature and therefore promises early diagnosis and sufficient monitoring in ophthalmology. However, there is considerable variability between experts analysing this data. Measures for quantitative assessment of the vasculature need to be developed and established, such as fractal dimension. Fractal dimension can be used to assess the complexity of vessels and has been shown to be independently associated with neovascularization, a symptom of diseases such as diabetic retinopathy. This investigation assessed the performance of three fractal dimension algorithms: Box Counting Dimension (BCD), Information Dimension (ID), and Differential Box Counting (DBC). Two of those, BCD and ID, rely on previous vessel segmentation. Assessment of the added value or disturbance regarding the segmentation step is a second aim of this study. The investigation was performed on a data set composed of 9 in vivo human eyes. Since there is no ground truth available, the performance of the methods in differentiating the Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC) layers apart and the consistency of measurements of the same layer at different time-points were tested. The performance parameters were the ICC and the Mann- Whitney U tests. The three applied methods were suitable to tell the different layers apart and showed consistent values applied in the same slab. Within the consistency test, the non-segmentation-based method, DBC, was found to be less accurate, expressed in a lower ICC value, compared to its segmentation-based counterparts. This result is thought to be due to the DBC’s higher sensitivity when compared to the other methods. This higher sensitivity might help detect changes in the microvasculature, like neovascularization, but is also more likely prone to noise and artefacts.
Adaptation of the Calcium-dependent Tension Development in Ventricular Cardiomyocytes
Authors: Appel Stephanie , Gerach Tobias , Dössel Olaf , Loewe Axel
Published: December 2021

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Dry vs. wet testing: quasi-static tensile experiment setup for polymer based biomaterials
Authors: Arbeiter Daniela , Oschatz Stefan , Lebahn Kerstin , Illner Sabine , Grabow Niels
Published: December 2021

Polymer materials can be manufactured with high reproducibility and do offer the potential for chemical modification. This enables matrix property modification and fine-tuning of several material characteristics, such as tissue-implant interaction, inflammatory potential or susceptibility to biofilm formation. Whereas manufacturing protocols are crucial for the resulting material properties, also the evaluation in terms of performance and safety has to be considered. Regarding this, both, temperature and composition of test medium may affect the physicochemical properties of implant materials. The present study addresses the influence of test medium compared to dry test conditions, each at two different temperatures, on the mechanical properties of elastomeric film and nonwoven materials.
Fiber statistics of nonwoven materials by SEM images - influence of number of images
Authors: Götz Andreas , Grabow Niels , Illner Sabine , Senz Volkmar
Published: December 2021

Electrospun nonwovens are widely applied in biomedicine and various other fields. For control of the manufacturing process and quality assurance Scanning electron microscopy (SEM) imaging is one standard practice. In this study, statistical datasets of 60 SEM images of three nonwoven samples were evaluated using Gaussian fit to obtain numerical results of their fiber diameter distributions. The question of how much effort is required for acceptable imaging and processing is being discussed. As determined here, for reliable statistics, a minimum surface area of the nonwoven has to be evaluated. The fiber diameter should be in a range of approximately 2 - 3% of the edge length of the square equivalent of the evaluated image area, using sufficiently magnified SEM images, in which the fiber diameter is imaged over at least 30 pixels.
Fiber composite materials via coaxial, dual or blend electrospinning
Authors: Illner Sabine , Sühr Michelle , Fiedler Nicklas , Arbeiter Daniela , Götz Andreas , Schmitz Klaus-Peter , Grabow Niels
Published: December 2021

Electrospinning (ES) is a suitable and cost effective method to mimic the chemical composition, morphology, and functional surface of natural tissues, for example of the nervous, dermal, vascular, and musculoskeletal systems. This technique is a versatile tool to obtain tailored fibrous scaffolds from various polymer materials. By varying the diameter, porosity, orientation, layering, surface structuring, mechanical properties and biodegradability of the fibers the properties can be adapted for specific applications ranging from implantable medical devices to wound repair and protective clothing. Especially the combination of different polymer types offers a high potential. In this study electrospun two-component nonwoven structures of thermoplastic copolyester elastomer (TPC-ET) and bioresorbable polylactide (PLLA) were fabricated, using different ES setups. A comparative evaluation in terms of porosity, thermal and mechanical properties as well as required fabrication effort, was performed. Nonwovens made from polymer blends and coaxial spun core-sheath fibers showed similar tensile strength, which was higher than dual electrospun fabrics. Porosity was found to be in the range of 80 - 90%. By modifying the polymer solution and process parameters multicomponent nonwoven structures with tailored properties and drug release profiles can be manufactured.
Cardiovascular, ophthalmologic and otolaryngologic medical device innovations – Progress report 2021 from the Twenty20 consortium RESPONSE
Authors: Grabow Niels , Senz Volkmar , Schmitz Klaus-Peter
Published: December 2021

The coordinated research project “RESPONSE - Partnership for Innovation in Implant Technology”, which is one of ten BMBF-funded research consortia within the program “Twenty20 - Partnership for Innovation”, is active in the field of medical device innovation. The consortium is currently in the process of unfolding its transfer phase. This involves a portfolio of key innovations for novel medical devices, technologies and processes. Also, RESPONSE is aiming at participative technology development, integrating perspectives of patients, developers, as well as systems and innovation researchers. Particular challenges are arising from the current re-prioritization and re-scheduling of project roadmaps in order to manage and alleviate the effects of the corona crisis.
Real-Time Multirate Filtering of Digitized Torque Signals on Tiva Microcontroller using Fixed-Point Design with MATLAB
Authors: Wilkie Jack A. , Stieglitz Thomas , Moeller Knut
Published: December 2021

Correct bone screw torque is critical for positive patient outcomes after orthopaedic surgery. Models of the screwing process have been developed to allow a smart screwdriver to optimise the insertion torque. Experimental data is required to test these models, so a test-rig has been developed. Accurate torque measurement is a key part of the test-rig. An FIR filter was designed for this torque signal, implemented on the test-rig, and compared theoretically and experimentally to a mean filter and to no filtering. The FIR and mean filters both performed well, with the FIR achieving better theoretical results, and the mean filter achieving better experimental results. Better understanding of the noise structure and potential signal distortion would be required to improve the FIR filter or to conclusively compare it against the mean filter, however both perform sufficiently well for this application.
Automated differentiation of Alzheimer’s condition using Kernel Density Estimation based texture analysis of single slice brain MR images
Authors: Veluppal Amrutha , Sadhukhan Deboleena , Gopinath Venugopal , Swaminathan Ramakrishnan
Published: December 2021

Computer-assisted tools can aid in the detection of Alzheimer disease (AD) which is a progressive neurodegenerative disorder that can lead to cognitive impairments and eventually death. The accumulated effects due to AD can cause changes in the appearance of grey matter, white matter and cerebrospinal fluid in brain Magnetic Resonance (MR) images. This study aims to use Kernel Density Estimation (KDE) technique to analyse the textural changes from single slice brain MR images for the detection of AD. The preprocessed, skull stripped T1-weighted MR brain images are obtained from the publicly available OASIS database. A single axial slice per subject is chosen from a volumetric image for further processing to reduce the computational load. Multivariate KDE technique is applied to each pixel, by considering the changes in the neighbourhood based on selected bandwidth to obtain corresponding density estimates. Statistical features quantifying the distribution of density estimates are extracted to characterise textural variations in images. Linear discriminant analysis (LDA) classifier is implemented with ten-fold cross-validation for detecting AD. An optimum bandwidth of 18 for the KDE technique is selected based on the classification performance. Out of seven extracted texture features, three are found to be statistically significant in distinguishing AD. The classification with LDA yields an accuracy of 72.3% with a sensitivity of 80.6% for identifying AD from healthy subjects. The proposed method is efficient in detecting AD by revealing the textural changes within the brain slice without the involvement of any segmentation technique. Thus, the novel KDE-based texture analysis proves to be an effective tool for the automated diagnosis of AD from single slice brain MR images.
Acoustic-kinetic joint analysis: Synchronization and Evaluation of kinetic measurement data in AEA (Acoustic Emission Analysis) based diagnosis of arthritic knee joint defects
Authors: Subke Jörg , Schneider Benedict , Hanitz Fiona , Wolff Udo
Published: December 2021

During a clinical study the AEA (Acoustic Emission Analysis) of arthritic defects in the knee joint was enhanced by the addition of kinetic measurement data. This enhanced AEA based method permits a non-invasive diagnosis and assessment of arthritic joint damage at an early stage. The diagnostic procedure includes three separate measurements that contribute in different ways to an extended diagnosis of the disease pattern [1, 2, 3]. During a series of three knee bends a force plate provides data of the ground force while a video-based gait analysis records the corresponding movement and the angles of hip-, knee-, and ankle joints. At the same time AEA detects the acoustic anomalies of damaged cartilage and the absolute angle of the system. The patterns of the kinetic data were analyzed to define the instants of time to correlate the data of the 3 measurement systems. The analysis of the force data yields a pattern with 8 phases. By means of the stance phase between the knee bends the instants of time are used to synchronize force and video based data. In the second step the synchronization of video based data was done by means of the absolute angle of the AEA system [4, 5]. The superposition of kinetic data and the acoustic emission permits a preliminary graphic representation and assessment of the measurement data. The procedure will be applied for the analysis of patients in a clinical study
Insights of posture dependent pressure characteristics in five rats
Authors: Flürenbrock Fabian , Schwander Simone , Podgoršak Anthony , Bausch Britta , Seebeck Petra , Zeilinger Melanie , Schmid Daners Marianne
Published: December 2021

Current shunt treatments of hydrocephalus, a condition characterized by excessive accumulation of cerebrospinal fluid (CSF) and intracranial pressure (ICP) fluctuations, suffer malfunctions caused by changes in patient’s posture. Research toward a quantitative model describing posture dependent dynamics of CSF related pressures such as ICP and blood pressure (BP) shall provide relevant information that can lead to a better understanding of CSF dynamics and thus, improved treatment outcomes. In this pilot study, ICP and femoral blood pressure (FBP) were measured concurrently in anaesthetized as well as awake and freely moving rats using radio telemetry. It was shown that despite the inherent challenges of limited space for sensor implants and rapid movements leading to strong artefacts, influences on CSF related pressure fluctuations due to posture changes can be observed in individual rats
Is User Experience a suitable goal in the development of medical devices?
Authors: Reisemann Matthias , Krupp Angelina
Published: December 2021

Product development in medical technology is largely governed by Regulatory Affairs. In contrast, for consumer products Human-Centred Design (HCD) is the guiding principle. Both approaches are laid down in international standards and overlap many aspects such as procedure, applied methodologies and development activities. For medical devices patient safety and therefore risk management is the guiding development goal. In HCD the focus lies on User Experience (UX), a positive experience throughout the entire product life cycle. The question arises whether UX could play a more important role in medical device development, particularly considering the similarities of the two development processes
Comparative analysis of alignment tools for application on Nanopore sequencing data
Authors: Becht Chiara , Schmidt Jonas , Blessing Frithjof , Wenzel Folker
Published: December 2021

INTRODUCTION: Long-read sequencing techniques such as Oxford Nanopore sequencing, are representing a promising novel approach in molecular-biological methodology, enabling potential facilitation in mapping and de novo assembly. In comparison to conventional sequencing methods, novel alignment tools are mandated to compensate differing data structures (especially high error rate) to achieve acceptably accurate analysis results. METHODS: In this study, benchmarking for long read aligners BLASR, GraphMap, LAST, minimap2, NGMLR and the short-read aligner BWA MEM on three experimental datasets was conducted. Obtained alignment results were compared for various quality and performance criteria, such as match rate, mismatch rate, error rate, working memory usage and computational time. RESULTS: The comparison yielded differences in alignment quality and performance of tools under test. Tool LAST showed the largest differences among all tools. Minimap2 achieved constant quality with good performance. BLASR, GraphMap, BWA MEM and NGMLR showed slight differences only. CONCLUSION: Differences among the tools could be reasoned with dataset characteristics and algorithm approaches of individual tools. All tools except BLASR seem applicable for Nanopore sequencing data. Therefore, selection of the tool should be done under consideration of the experimental design and the further downstream analysis
Angiogenesis by BMP-2-PDLLA-Biohybrids in Co-Culture with Osteoblasts and Endothelia
Authors: Dohle Eva , Sowislok Andrea , Ghanaati Shahram , Jennissen Herber P.
Published: December 2021

Adsorbate biohybrids for BMP-2 delivery based on electrospun PDLLA-nanofiber fleeces loaded with 0.6 μg/cm2 rhBMP-2COL (E. coli) strongly induced microvessel- like structures when incubated for 14 days in cocultures of human outgrowth endothelial cells (OEC) together with human primary osteoblasts (pOB). Higher loaded rhBMP-2COL biohybrids (4.6 μg/cm2) were low- to noninductive. Adsorbate biohybrids of rhBMP-2CHO (CHO cells) loaded with 1.0-6.0 μg/cm2 induced only a classic cobblestone- like growth pattern without any microvessels. Concentration- response experiments (7 days) indicate a binding affinity of rhBMP-2COL for microvessel induction in the picomolar range with nanomolar concentrations being non-inductive