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A Robust Interface for Head Motion based Control of a Robot Arm using MARG and Visual Sensors
(2018)
Head-controlled human machine interfaces have gained popularity over the past years, especially in the restoration of the autonomy of severely disabled people, like tetraplegics. These interfaces need to be reliable and robust regarding the environmental conditions to guarantee safety of the user and enable a direct interaction between a human and a machine. This paper presents a hybrid MARG and visual sensor system for head orientation estimation which is in this case used to teleoperate a robotic arm. The system contains a Magnetic Angular Rate Gravity (MARG)-sensor and a Tobii eye tracker 4C. A MARG sensor consists of tri-axis accelerometer, gyroscope as well as a magnetometer which enable a complete measurement of orientation relative to the direction of gravity and magnetic field of the earth. The tri-axis magnetometer is sensitive to external magnetic fields which result in incorrect orientation estimation from the sensor fusion process. In this work the Tobii eye tracker 4C is used to increase head orientation estimation because it also features head tracking even though it is commonly used for eye tracking. This type of visual sensor does not suffer magnetic drift. However, it computes orientation data only, if a user is detectable. Within this work a state machine is presented which enables data fusion of the MARG and visual sensor to improve orientation estimation. The fusion of the orientation data of MARG and visual sensors enables a robust interface, which is immune against external magnetic fields. Therefore, it increases the safety of the human machine interaction.
It is well-known that protein-modified implant surfaces such as TiO2 show a higher bioconductivity. Fibronectin is a glycoprotein from the extracellular matrix (ECM) with a major role in cell adhesion. It can be applied on titanium oxide surfaces to accelerate implant integration. Not only the surface concentration but also the presentation of the protein plays an important role for the cellular response. We were able to show that TiOX surfaces modified with biotinylated fibronectin adsorbed on a streptavidin-silane self-assembly multilayer system are more effective regarding osteoblast adhesion than surfaces modified with nonspecifically bound fibronectin. The adsorption and conformation behavior of biotinylated and nonbiotinylated (native) fibronectin was studied by surface plasmon resonance (SPR) spectroscopy and atomic force microscopy (AFM). Imaging of the protein modification revealed that fibronectin adopts different conformations on nonmodified compared to streptavidin-modified TiOX surfaces. This conformational change of biotinylated fibronectin on the streptavidin monolayer delivers a fibronectin structure similar to the conformation inside the ECM and therefore explains the higher cell affinity for these surfaces.
Biofunktionalisierung von Titanimplantaten mit einem Multilayersystem aus BMP-2 und Fibronektin
(2016)
CIP is an open-source high-level function library for (non-linear) curve fitting and data smoothing (with cubic splines), clustering (k-medoids, ART-2a) and machine learning (multiple linear/polynomial regression, feed-forward perceptron-type shallow and deep neural networks and support vector machines). In addition it provides several heuristics for the selection of training and test data or methods to estimate the relevance of data input components. CIP is built on top of the computing platform Mathematica to exploit its algorithmic and graphical capabilities.
CIP is an open-source high-level function library for (non-linear) curve fitting and data smoothing (with cubic splines), clustering (k-medoids, ART-2a) and machine learning (multiple linear/polynomial regression, feed-forward perceptron-type shallow and deep neural networks and support vector machines). In addition it provides several heuristics for the selection of training and test data or methods to estimate the relevance of data input components. CIP is built on top of the computing platform Mathematica to exploit its algorithmic and graphical capabilities.
The wireless data logger system “Cor/log® BAN BT” (CL) allows seamless 24/7 monitoring of relevant vital sign parameters. CL covers the entire period of acute point of care inside the hospital and the recovery period, when first mobility is achieved and when the patient is released into an ambulatory or homecare environment. The CL records the relevant vital signs such as ECG, respiration, pulse oximetry with plethysmogram and movement. The vital data collected with the CL data logger is saved on a memory card for further analysis and is simultaneously transmitted in real-time to a telemedicine server via a smartphone or tablet. The smartphone also provides GPS location information. In addition Cor/log View, an Android Application for viewing recorded vital sign data originating from the CL, was developed. CL has also a connector to the generic MedM health cloud. MedM is a generic patient data management system (PDMS) consisting of a cloud portal and a mobile health app. The app runs on Android, iOS and Windows. The app can connects wirelessly to the CL physiologic monitor and stores the vital signs in the cloud.
Creating chemo- & bioinformatics workflows, further developments within the CDK-Taverna Project
(2008)
The algorithm for automated functional groups detection and extraction of organic molecules developed by Peter Ertl is implemented on the basis of the Chemistry Development Kit (CDK).
Folder Basic contains the basic ErtlFunctionalGroupsFinder code and test code for integration in Java projects.
Folder CDK contains CDK library jar file cdk-2.2.jar that ErtlFunctionalGroupsFinder works with.
Folder Evaluation contains sample code for evaluation of functional groups with ErtlFunctionalGroupsFinder.
Folder JUnit 4 contains library jar files for unit testing.
Folder Performance contains a jar library for performance tests.
ErtlFunctionalGroupsFinder is described in the scientific literature