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Background and Objective
Effective leg extension training at a leg press requires high forces, which need to be controlled to avoid training-induced damage. In order to avoid high external knee adduction moments, which are one reason for unphysiological loadings on knee joint structures, both training movements and the whole reaction force vector need to be observed. In this study, the applicability of lateral and medial changes in foot orientation and position as possible manipulated variables to control external knee adduction moments is investigated. As secondary parameters both the medio-lateral position of the center of pressure and the frontal-plane orientation of the reaction force vector are analyzed.
Methods
Knee adduction moments are estimated using a dynamic model of the musculoskeletal system together with the measured reaction force vector and the motion of the subject by solving the inverse kinematic and dynamic problem. Six different foot conditions with varying positions and orientations of the foot in a static leg press are evaluated and compared to a neutral foot position.
Results
Both lateral and medial wedges under the foot and medial and lateral shifts of the foot can influence external knee adduction moments in the presented study with six healthy subjects. Different effects are observed with the varying conditions: the pose of the leg is changed and the direction and center of pressure of the reaction force vector is influenced. Each effect results in a different direction or center of pressure of the reaction force vector.
Conclusions
The results allow the conclusion that foot position and orientation can be used as manipulated variables in a control loop to actively control knee adduction moments in leg extension training.
Robotergestütztes System für ein verbessertes neuromuskuläres Aufbautraining der Beinstrecker
(2016)
Neuromuskuläres Aufbautraining der Beinstrecker ist ein wichtiger Bestandteil in der Rehabilitation und Prävention von Muskel-Skelett-Erkrankungen. Effektives Training erfordert hohe Muskelkräfte, die gleichzeitig hohe Belastungen von bereits geschädigten Strukturen bedeuten. Um trainingsinduzierte Schädigungen zu vermeiden, müssen diese Kräfte kontrolliert werden. Mit heutigen Trainingsgeräten können diese Ziele allerdings nicht erreicht werden. Für ein sicheres und effektives Training sollen durch den Einsatz der Robotik, Sensorik, eines Regelkreises sowie Muskel-Skelett-Modellen Belastungen am Zielgewebe direkt berechnet und kontrolliert werden. Auf Basis zweier Vorstudien zu möglichen Stellgrößen wird der Aufbau eines robotischen Systems vorgestellt, das sowohl für Forschungszwecke als auch zur Entwicklung neuartiger Trainingsgeräte verwendet werden kann.
Hintergrund
Die Anwendung und das Verständnis von Statistik sind sehr wichtig für die biomedizinische Forschung und für die klinische Praxis. Dies gilt insbesondere auch zur Abschätzung der Möglichkeiten unterschiedlichster Diagnostik- und Therapieoptionen beim Glaukom. Die scheinbare Komplexität der Statistik, die zum Teil dem „gesunden Menschenverstand“ zu widersprechen scheint, zusammen mit der nur vorsichtigen Akzeptanz der Statistik bei vielen Medizinern können zu bewussten und unbewussten Manipulationen bei der Datendarstellung und -interpretation führen.
Ziel der Arbeit
Ziel ist die verständliche Darstellung einiger typischer Fehler in der medizinisch-statistischen Datenbehandlung.
Material und Methoden
Anhand hypothetischer Beispiele aus der Glaukomdiagnostik erfolgen die Darstellung der Wirkung eines hypotensiven Medikamentes sowie die Beurteilung der Ergebnisse eines diagnostischen Tests. Es werden die typischsten statistischen Einsatzbereiche und Irrtumsquellen ausführlich und verständlich analysiert
Ergebnisse
Mechanismen von Datenmanipulation und falscher Dateninterpretation werden aufgeklärt. Typische Irrtumsquellen bei der statistischen Auswertung und Datendarstellung werden dabei erläutert.
Schlussfolgerungen
Die erläuterten praktischen Beispiele zeigen die Notwendigkeit, die Grundlagen der Statistik zu verstehen und korrekt anwenden zu können. Fehlendes Grundlagenwissen und Halbwissen der medizinischen Statistik können zu folgenschweren Missverständnissen und falschen Entscheidungen in der medizinischen Forschung, aber auch in der klinischen Praxis führen.
The Saturnian moon Enceladus with its extensive water bodies underneath a thick ice sheet cover is a potential candidate for extraterrestrial life. Direct exploration of such extraterrestrial aquatic ecosystems requires advanced access and sampling technologies with a high level of autonomy. A new technological approach has been developed as part of the collaborative research project Enceladus Explorer (EnEx). The concept is based upon a minimally invasive melting probe called the IceMole. The force-regulated, heater-controlled IceMole is able to travel along a curved trajectory as well as upwards. Hence, it allows maneuvers which may be necessary for obstacle avoidance or target selection. Maneuverability, however, necessitates a sophisticated on-board navigation system capable of autonomous operations. The development of such a navigational system has been the focal part of the EnEx project. The original IceMole has been further developed to include relative positioning based on in-ice attitude determination, acoustic positioning, ultrasonic obstacle and target detection integrated through a high-level sensor fusion. This paper describes the EnEx technology and discusses implications for an actual extraterrestrial mission concept.
Analysis of the long-term effect of the MBST® nuclear magnetic resonance therapy on gonarthrosis
(2016)
Light-addressable potentiometric sensor as a sensing element in plug-based microfluidic devices
(2016)
A plug-based microfluidic system based on the principle of the light-addressable potentiometric sensor (LAPS) is proposed. The LAPS is a semiconductor-based chemical sensor, which has a free addressability of the measurement point on the sensing surface. By combining a microfluidic device and LAPS, ion sensing can be performed anywhere inside the microfluidic channel. In this study, the sample solution to be measured was introduced into the channel in a form of a plug with a volume in the range of microliters. Taking advantage of the light-addressability, the position of the plug could be monitored and pneumatically controlled. With the developed system, the pH value of a plug with a volume down to 400 nL could be measured. As an example of plug-based operation, two plugs were merged in the channel, and the pH change was detected by differential measurement.
Visualization of the recovery process of defects in a cultured cell layer by chemical imaging sensor
(2016)
The chemical imaging sensor is a field-effect sensor which is able to visualize both the distribution of ions (in LAPS mode) and the distribution of impedance (in SPIM mode) in the sample. In this study, a novel cell assay is proposed, in which the chemical imaging sensor operated in SPIM mode is applied to monitor the recovery of defects in a cell layer brought into proximity of the sensing surface. A reduced impedance at a defect formed artificially in a cell layer was successfully visualized in a photocurrent image. The cell layer was cultured over two weeks, during which the temporal change of the photocurrent distribution corresponding to the recovery of the defect was observed.
An amperometric biosensor using a substrate recycling principle was realized for the detection of low adrenaline concentrations (1 nM) by measurements in phosphate buffer and Ringer’s solution at pH 6.5 and pH 7.4, respectively. In proof-of-concept experiments, a Boolean logic-gate principle has been applied to develop a digital adrenaline biosensor based on an enzyme AND logic gate. The obtained results demonstrate that the developed digital biosensor is capable for a rapid qualitative determination of the presence/absence of adrenaline in a YES/NO statement. Such digital biosensor could be used in clinical diagnostics for the control of a correct insertion of a catheter in the adrenal veins during adrenal venous-sampling procedure.
In this study, we show that synthetic sapphire (Al₂O₃), an established implant material, can also serve as a platform material for biosensors comparable to nanocrystalline diamond. Sapphire chips, beads, and powder were first modified with (3-aminopropyl) triethoxysilane (APTES), followed by succinic anhydride (SA), and finally single-stranded probe DNA was EDC coupled to the functionalized layer. The presence of the APTES-SA layer on sapphire powders was confirmed by thermogravimetric analyis and Fourier-transform infrared spectroscopy. Using planar sapphire chips as substrates and X-ray photoelectron spectroscopy (XPS) as surface-sensitive tool, the sequence of individual layers was analyzed with respect to their chemical state, enabling the quantification of areal densities of the involved molecular units. Fluorescence microscopy was used to demonstrate the hybridization of fluorescently tagged target DNA to the probe DNA, including denaturation- and re-hybridization experiments. Due to its high thermal conductivity, synthetic sapphire is especially suitable as a chip material for the heat-transfer method, which was employed to distinguish complementary- and non-complementary DNA duplexes containing single-nucleotide polymorphisms. These results indicate that it is possible to detect mutations electronically with a chemically resilient and electrically insulating chip material.
We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.
Label-free Electrostatic Detection of DNA Amplification by PCR Using Capacitive Field-effect Devices
(2016)
A capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensor modified with a positively charged weak polyelectrolyte of poly(allylamine hydrochloride) (PAH)/single-stranded probe DNA (ssDNA) bilayer has been used for a label-free electrostatic detection of pathogen-specific DNA amplification via polymerase chain reaction (PCR). The sensor is able to distinguish between positive and negative PCR solutions, to detect the existence of target DNA amplicons in PCR samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process.
Purpose
Two semi-empirical models were recently published, both making use of existing literature data, but each taking into account different physical phenomena that trigger hemolysis. In the first model, hemoglobin (Hb) release is described as a permeation procedure across the membrane, assuming a shear stress-dependent process (sublethal model). The second model only accounts for hemoglobin release that is caused by cell membrane breakdown, which occurs when red blood cells (RBC) undergo mechanically induced shearing for a period longer than the threshold time (nonuniform threshold model). In this paper, we introduce a model that considers the hemolysis generated by both these possible phenomena.
Methods
Since hemolysis can possibly be caused by permeation of hemoglobin through the RBC functional membrane as well as by release of hemoglobin from RBC membrane breakdown, our proposed model combines both these models. An experimental setup consisting of a Couette device was utilized for validation of our proposed model.
Results
A comparison is presented between the damage index (DI) predicted by the proposed model vs. the sublethal model vs. the nonthreshold model and experimental datasets. This comparison covers a wide range of shear stress for both human and porcine blood. An appropriate agreement between the measured DI and the DI predicted by the present model was obtained.
Conclusions
The semiempirical hemolysis model introduced in this paper aims for significantly enhanced conformity with experimental data. Two phenomenological outcomes become possible with the proposed approach: an estimation of the average time after which cell membrane breakdown occurs under the applied conditions, and a prediction of the ratio between the phenomena involved in hemolysis.
Für die Verarbeitung von natürlicher Sprache ist ein wichtiger Zwischenschritt das Parsing, bei dem für Sätze der natürlichen Sprache Ableitungsbäume bestimmt werden. Dieses Verfahren ist vergleichbar zum Parsen formaler Sprachen, wie z. B. das Parsen eines Quelltextes. Die Parsing-Methoden der formalen Sprachen, z. B. Bottom-up-Parser, können nicht auf das Parsen der natürlichen Sprache übertragen werden, da keine Formalisierung der natürlichen Sprachen existiert [3, 12, 23, 30].
In den ersten Programmen, die natürliche Sprache verarbeiten [32, 41], wurde versucht die natürliche Sprache mit festen Regelmengen zu verarbeiten. Dieser Ansatz stieß jedoch schnell an seine Grenzen, da die Regelmenge nicht vollständig sowie nicht minimal ist und wegen der benötigten Menge an Regeln schwer zu verwalten ist. Die Korpuslinguistik [22] bot die Möglichkeit, die Regelmenge durch Supervised-Machine-Learning-Verfahren [2] abzulösen.
Teil der Korpuslinguistik ist es, große Textkorpora zu erstellen und diese mit sprachlichen Strukturen zu annotieren. Zu diesen Strukturen gehören sowohl die Wortarten als auch die Ableitungsbäume der Sätze. Vorteil dieser Methodik ist es, dass repräsentative Daten zur Verfügung stehen. Diese Daten werden genutzt, um mit Supervised-Machine-Learning-Verfahren die Gesetzmäßigkeiten der natürliche Sprachen zu erlernen.
Das Maximum-Entropie-Verfahren ist ein Supervised-Machine-Learning-Verfahren, das genutzt wird, um natürliche Sprache zu erlernen. Ratnaparkhi [25] nutzt Maximum-Entropie, um Ableitungsbäume für Sätze der natürlichen Sprache zu erlernen. Dieses Verfahren macht es möglich, die natürliche Sprache (abgebildet als Σ∗) trotz einer fehlenden formalen Grammatik zu parsen.
Smoothed Finite Element Methods for Nonlinear Solid Mechanics Problems: 2D and 3D Case Studies
(2016)
The Smoothed Finite Element Method (SFEM) is presented as an edge-based and a facebased techniques for 2D and 3D boundary value problems, respectively. SFEMs avoid shortcomings of the standard Finite Element Method (FEM) with lower order elements such as overly stiff behavior, poor stress solution, and locking effects. Based on the idea of averaging spatially the standard strain field of the FEM over so-called smoothing domains SFEM calculates the stiffness matrix for the same number of degrees of freedom (DOFs) as those of the FEM. However, the SFEMs significantly improve accuracy and convergence even for distorted meshes and/or nearly incompressible materials.
Numerical results of the SFEMs for a cardiac tissue membrane (thin plate inflation) and an artery (tension of 3D tube) show clearly their advantageous properties in improving accuracy particularly for the distorted meshes and avoiding shear locking effects.