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2017


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Editorial for the Special Issue on Microdevices and Microsystems for Cell Manipulation

Hu, W., Ohta, A. T.

8, Multidisciplinary Digital Publishing Institute, September 2017 (misc)

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DOI [BibTex]

2017


DOI [BibTex]


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Parameterized Model of 2D Articulated Human Shape

Black, M. J., Freifeld, O., Weiss, A., Loper, M., Guan, P.

September 2017, U.S.~Patent 9,761,060 (misc)

Abstract
Disclosed are computer-readable devices, systems and methods for generating a model of a clothed body. The method includes generating a model of an unclothed human body, the model capturing a shape or a pose of the unclothed human body, determining two-dimensional contours associated with the model, and computing deformations by aligning a contour of a clothed human body with a contour of the unclothed human body. Based on the two-dimensional contours and the deformations, the method includes generating a first two-dimensional model of the unclothed human body, the first two-dimensional model factoring the deformations of the unclothed human body into one or more of a shape variation component, a viewpoint change, and a pose variation and learning an eigen-clothing model using principal component analysis applied to the deformations, wherein the eigen-clothing model classifies different types of clothing, to yield a second two-dimensional model of a clothed human body.

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Google Patents [BibTex]


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Physical and Behavioral Factors Improve Robot Hug Quality

Block, A. E., Kuchenbecker, K. J.

Workshop Paper (2 pages) presented at the RO-MAN Workshop on Social Interaction and Multimodal Expression for Socially Intelligent Robots, Lisbon, Portugal, August 2017 (misc)

Abstract
A hug is one of the most basic ways humans can express affection. As hugs are so common, a natural progression of robot development is to have robots one day hug humans as seamlessly as these intimate human-human interactions occur. This project’s purpose is to evaluate human responses to different robot physical characteristics and hugging behaviors. Specifically, we aim to test the hypothesis that a warm, soft, touch-sensitive PR2 humanoid robot can provide humans with satisfying hugs by matching both their hugging pressure and their hugging duration. Thirty participants experienced and evaluated twelve hugs with the robot, divided into three randomly ordered trials that focused on physical robot char- acteristics and nine randomly ordered trials with varied hug pressure and duration. We found that people prefer soft, warm hugs over hard, cold hugs. Furthermore, users prefer hugs that physically squeeze them and release immediately when they are ready for the hug to end.

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Project Page [BibTex]

Project Page [BibTex]


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Crowdshaping Realistic 3D Avatars with Words

Streuber, S., Ramirez, M. Q., Black, M., Zuffi, S., O’Toole, A., Hill, M. Q., Hahn, C. A.

August 2017, Application PCT/EP2017/051954 (misc)

Abstract
A method for generating a body shape, comprising the steps: - receiving one or more linguistic descriptors related to the body shape; - retrieving an association between the one or more linguistic descriptors and a body shape; and - generating the body shape, based on the association.

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Google Patents [BibTex]

Google Patents [BibTex]


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Robotic Motion Learning Framework to Promote Social Engagement

Burns, R.

The George Washington University, August 2017 (mastersthesis)

Abstract
This paper discusses a novel framework designed to increase human-robot interaction through robotic imitation of the user's gestures. The set up consists of a humanoid robotic agent that socializes with and play games with the user. For the experimental group, the robot also imitates one of the user's novel gestures during a play session. We hypothesize that the robot's use of imitation will increase the user's openness towards engaging with the robot. Preliminary results from a pilot study of 12 subjects are promising in that post-imitation, experimental subjects displayed a more positive emotional state, had higher instances of mood contagion towards the robot, and interpreted the robot to have a higher level of autonomy than their control group counterparts. These results point to an increased user interest in engagement fueled by personalized imitation during interaction.

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link (url) [BibTex]

link (url) [BibTex]


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Physically Interactive Exercise Games with a Baxter Robot

Fitter, N. T., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE World Haptics Conference (WHC), Munich, Germany, June 2017 (misc)

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Project Page [BibTex]

Project Page [BibTex]


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System and method for simulating realistic clothing

Black, M. J., Guan, P.

June 2017, U.S.~Patent 9,679,409 B2 (misc)

Abstract
Systems, methods, and computer-readable storage media for simulating realistic clothing. The system generates a clothing deformation model for a clothing type, wherein the clothing deformation model factors a change of clothing shape due to rigid limb rotation, pose-independent body shape, and pose-dependent deformations. Next, the system generates a custom-shaped garment for a given body by mapping, via the clothing deformation model, body shape parameters to clothing shape parameters. The system then automatically dresses the given body with the custom- shaped garment.

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Google Patents pdf [BibTex]


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Proton Pack: Visuo-Haptic Surface Data Recording

Burka, A., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE World Haptics Conference (WHC), Munich, Germany, June 2017 (misc)

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Project Page [BibTex]

Project Page [BibTex]


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Teaching a Robot to Collaborate with a Human Via Haptic Teleoperation

Hu, S., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Munich, Germany, June 2017 (misc)

hi

Project Page [BibTex]

Project Page [BibTex]


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How Should Robots Hug?

Block, A. E., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Munich, Germany, June 2017 (misc)

hi

Project Page [BibTex]

Project Page [BibTex]


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An Interactive Augmented-Reality Video Training Platform for the da Vinci Surgical System

Carlson, J., Kuchenbecker, K. J.

Workshop paper (3 pages) presented at the ICRA Workshop on C4 Surgical Robots, Singapore, May 2017 (misc)

Abstract
Teleoperated surgical robots such as the Intuitive da Vinci Surgical System facilitate minimally invasive surgeries, which decrease risk to patients. However, these systems can be difficult to learn, and existing training curricula on surgical simulators do not offer students the realistic experience of a full operation. This paper presents an augmented-reality video training platform for the da Vinci that will allow trainees to rehearse any surgery recorded by an expert. While the trainee operates a da Vinci in free space, they see their own instruments overlaid on the expert video. Tools are identified in the source videos via color segmentation and kernelized correlation filter tracking, and their depth is calculated from the da Vinci’s stereoscopic video feed. The user tries to follow the expert’s movements, and if any of their tools venture too far away, the system provides instantaneous visual feedback and pauses to allow the user to correct their motion. The trainee can also rewind the expert video by bringing either da Vinci tool very close to the camera. This combined and augmented video provides the user with an immersive and interactive training experience.

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[BibTex]

[BibTex]


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Human Shape Estimation using Statistical Body Models

Loper, M. M.

University of Tübingen, May 2017 (thesis)

Abstract
Human body estimation methods transform real-world observations into predictions about human body state. These estimation methods benefit a variety of health, entertainment, clothing, and ergonomics applications. State may include pose, overall body shape, and appearance. Body state estimation is underconstrained by observations; ambiguity presents itself both in the form of missing data within observations, and also in the form of unknown correspondences between observations. We address this challenge with the use of a statistical body model: a data-driven virtual human. This helps resolve ambiguity in two ways. First, it fills in missing data, meaning that incomplete observations still result in complete shape estimates. Second, the model provides a statistically-motivated penalty for unlikely states, which enables more plausible body shape estimates. Body state inference requires more than a body model; we therefore build obser- vation models whose output is compared with real observations. In this thesis, body state is estimated from three types of observations: 3D motion capture markers, depth and color images, and high-resolution 3D scans. In each case, a forward process is proposed which simulates observations. By comparing observations to the results of the forward process, state can be adjusted to minimize the difference between simulated and observed data. We use gradient-based methods because they are critical to the precise estimation of state with a large number of parameters. The contributions of this work include three parts. First, we propose a method for the estimation of body shape, nonrigid deformation, and pose from 3D markers. Second, we present a concise approach to differentiating through the rendering process, with application to body shape estimation. And finally, we present a statistical body model trained from human body scans, with state-of-the-art fidelity, good runtime performance, and compatibility with existing animation packages.

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Official Version [BibTex]


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Hand-Clapping Games with a Baxter Robot

Fitter, N. T., Kuchenbecker, K. J.

Hands-on demonstration presented at ACM/IEEE International Conference on Human-Robot Interaction (HRI), Vienna, Austria, March 2017 (misc)

Abstract
Robots that work alongside humans might be more effective if they could forge a strong social bond with their human partners. Hand-clapping games and other forms of rhythmic social-physical interaction may foster human-robot teamwork, but the design of such interactions has scarcely been explored. At the HRI 2017 conference, we will showcase several such interactions taken from our recent work with the Rethink Robotics Baxter Research Robot, including tempo-matching, Simon says, and Pat-a-cake-like games. We believe conference attendees will be both entertained and intrigued by this novel demonstration of social-physical HRI.

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Project Page [BibTex]

Project Page [BibTex]


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Automatic OSATS Rating of Trainee Skill at a Pediatric Laparoscopic Suturing Task

Oquendo, Y. A., Riddle, E. W., Hiller, D., Blinman, T. A., Kuchenbecker, K. J.

Surgical Endoscopy, 31(Supplement 1):S28, Extended abstract presented as a podium presentation at the Annual Meeting of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), Springer, Houston, USA, March 2017 (misc)

Abstract
Introduction: Minimally invasive surgery has revolutionized surgical practice, but challenges remain. Trainees must acquire complex technical skills while minimizing patient risk, and surgeons must maintain their skills for rare procedures. These challenges are magnified in pediatric surgery due to the smaller spaces, finer tissue, and relative dearth of both inanimate and virtual simulators. To build technical expertise, trainees need opportunities for deliberate practice with specific performance feedback, which is typically provided via tedious human grading. This study aimed to validate a novel motion-tracking system and machine learning algorithm for automatically evaluating trainee performance on a pediatric laparoscopic suturing task using a 1–5 OSATS Overall Skill rating. Methods: Subjects (n=14) ranging from medical students to fellows per- formed one or two trials of an intracorporeal suturing task in a custom pediatric laparoscopy training box (Fig. 1) after watching a video of ideal performance by an expert. The position and orientation of the tools and endoscope were recorded over time using Ascension trakSTAR magnetic motion-tracking sensors, and both instrument grasp angles were recorded over time using flex sensors on the handles. The 27 trials were video-recorded and scored on the OSATS scale by a senior fellow; ratings ranged from 1 to 4. The raw motion data from each trial was processed to calculate over 200 preliminary motion parameters. Regularized least-squares regression (LASSO) was used to identify the most predictive parameters for inclusion in a regression tree. Model performance was evaluated by leave-one-subject-out cross validation, wherein the automatic scores given to each subject’s trials (by a model trained on all other data) are compared to the corresponding human rater scores. Results: The best-performing LASSO algorithm identified 14 predictive parameters for inclusion in the regression tree, including completion time, linear path length, angular path length, angular acceleration, grasp velocity, and grasp acceleration. The final model’s raw output showed a strong positive correlation of 0.87 with the reviewer-generated scores, and rounding the output to the nearest integer yielded a leave-one-subject-out cross-validation accuracy of 77.8%. Results are summarized in the confusion matrix (Table 1). Conclusions: Our novel motion-tracking system and regression model automatically gave previously unseen trials overall skill scores that closely match scores from an expert human rater. With additional data and further development, this system may enable creation of a motion-based training platform for pediatric laparoscopic surgery and could yield insights into the fundamental components of surgical skill.

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[BibTex]

[BibTex]


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How Much Haptic Surface Data is Enough?

Burka, A., Kuchenbecker, K. J.

Workshop paper (5 pages) presented at the AAAI Spring Symposium on Interactive Multi-Sensory Object Perception for Embodied Agents, Stanford, USA, March 2017 (misc)

Abstract
The Proton Pack is a portable visuo-haptic surface interaction recording device that will be used to collect a vast multimodal dataset, intended for robots to use as part of an approach to understanding the world around them. In order to collect a useful dataset, we want to pick a suitable interaction duration for each surface, noting the tradeoff between data collection resources and completeness of data. One interesting approach frames the data collection process as an online learning problem, building an incremental surface model and using that model to decide when there is enough data. Here we examine how to do such online surface modeling and when to stop collecting data, using kinetic friction as a first domain in which to apply online modeling.

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Enhancing Human-Computer Interaction via Electrovibration

Emgin, S. E., Sadia, B., Vardar, Y., Basdogan, C.

Demo in IEEE World Haptics, 2017 (misc)

Abstract
We present a compact tablet that displays electrostatic haptic feedback to the user. We track user?s finger position via an infrared frame and then display haptic feedback through a capacitive touch screen based on her/his position. In order to demonstrate practical utility of the proposed system, the following applications have been developed: (1) Online Shopping application allows users to be able to feel the cord density of two different fabrics. (2) Education application asks user to add two numbers by dragging one number onto another in order to match the sum. After selecting the first number, haptic feedback assists user to select the right pair. (3) Gaming/Entertainment application presents users a bike riding experience on three different road textures -smooth, bumpy, and sandy. (4) User Interface application in which users are asked to drag two visually identical folders. While dragging, users are able to differentiate the amount of data in each folder based on haptic resistance.

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[BibTex]

[BibTex]


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Change-point Detection and Kernels Methods

Garreau, D.

Ecole Normale Supérieure / PSL Research University, 2017 (thesis)

link (url) [BibTex]

link (url) [BibTex]


Thumb xl screen shot 2018 05 04 at 11.42.00
Reproduction of textures based on electrovibration

Fiedler, T., Vardar, Y., Strese, M., Steinbach, E., Basdogan, C.

Demo in IEEE World Haptics, 2017 (misc)

Abstract
This demonstration presents an approach to represent textures based on electovibration. We collect acceleration data which occurs while sliding a tool tip over a real texture surface. The prerecorded data was collected by a ADXL335 accelerometer, which is mounted on a FALCON device moving on the x-axis with a regulated velocity. In order to replicate the same acceleration with electrovibration, we found two problems. The frequency of one sine wave shifts to the double frequency. This effect originates from the electrostatic force between the finger pad and the tactile display as proposed by Kactmarek et Al. [1]. Taking the square root of the input signal corrects the effect. This was also earlier proposed by [1, 2, 3] However, if not only one but multiple sine waves are displayed interference occur and acceleration signals from real textures may not feel perceptually realistic. We propose to display only the dominant frequencies from a real texture signal. Peak frequencies are determined within the respect of the JND of 11 percent found by earlier literature. A new sine wave signal with the dominant frequencies is created. In the demo, we will let the attendees feel the differences between prerecorded and artificially created textures.

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[BibTex]

[BibTex]


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Learning Inference Models for Computer Vision

Jampani, V.

MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)

Abstract
Computer vision can be understood as the ability to perform 'inference' on image data. Breakthroughs in computer vision technology are often marked by advances in inference techniques, as even the model design is often dictated by the complexity of inference in them. This thesis proposes learning based inference schemes and demonstrates applications in computer vision. We propose techniques for inference in both generative and discriminative computer vision models. Despite their intuitive appeal, the use of generative models in vision is hampered by the difficulty of posterior inference, which is often too complex or too slow to be practical. We propose techniques for improving inference in two widely used techniques: Markov Chain Monte Carlo (MCMC) sampling and message-passing inference. Our inference strategy is to learn separate discriminative models that assist Bayesian inference in a generative model. Experiments on a range of generative vision models show that the proposed techniques accelerate the inference process and/or converge to better solutions. A main complication in the design of discriminative models is the inclusion of prior knowledge in a principled way. For better inference in discriminative models, we propose techniques that modify the original model itself, as inference is simple evaluation of the model. We concentrate on convolutional neural network (CNN) models and propose a generalization of standard spatial convolutions, which are the basic building blocks of CNN architectures, to bilateral convolutions. First, we generalize the existing use of bilateral filters and then propose new neural network architectures with learnable bilateral filters, which we call `Bilateral Neural Networks'. We show how the bilateral filtering modules can be used for modifying existing CNN architectures for better image segmentation and propose a neural network approach for temporal information propagation in videos. Experiments demonstrate the potential of the proposed bilateral networks on a wide range of vision tasks and datasets. In summary, we propose learning based techniques for better inference in several computer vision models ranging from inverse graphics to freely parameterized neural networks. In generative vision models, our inference techniques alleviate some of the crucial hurdles in Bayesian posterior inference, paving new ways for the use of model based machine learning in vision. In discriminative CNN models, the proposed filter generalizations aid in the design of new neural network architectures that can handle sparse high-dimensional data as well as provide a way for incorporating prior knowledge into CNNs.

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pdf [BibTex]

pdf [BibTex]


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Development and Evaluation of a Portable BCI System for Remote Data Acquisition

Emde, T.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

ei

[BibTex]

[BibTex]


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Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis

Fomina, T.

Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

ei

[BibTex]

[BibTex]


Thumb xl paraview preview
Design of a visualization scheme for functional connectivity data of Human Brain

Bramlage, L.

Hochschule Osnabrück - University of Applied Sciences, 2017 (thesis)

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Bramlage_BSc_2017.pdf [BibTex]


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Causal models for decision making via integrative inference

Geiger, P.

University of Stuttgart, Germany, 2017 (phdthesis)

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[BibTex]

[BibTex]


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Capturing Hand-Object Interaction and Reconstruction of Manipulated Objects

Tzionas, D.

University of Bonn, 2017 (phdthesis)

Abstract
Hand motion capture with an RGB-D sensor gained recently a lot of research attention, however, even most recent approaches focus on the case of a single isolated hand. We focus instead on hands that interact with other hands or with a rigid or articulated object. Our framework successfully captures motion in such scenarios by combining a generative model with discriminatively trained salient points, collision detection and physics simulation to achieve a low tracking error with physically plausible poses. All components are unified in a single objective function that can be optimized with standard optimization techniques. We initially assume a-priori knowledge of the object's shape and skeleton. In case of unknown object shape there are existing 3d reconstruction methods that capitalize on distinctive geometric or texture features. These methods though fail for textureless and highly symmetric objects like household articles, mechanical parts or toys. We show that extracting 3d hand motion for in-hand scanning effectively facilitates the reconstruction of such objects and we fuse the rich additional information of hands into a 3d reconstruction pipeline. Finally, although shape reconstruction is enough for rigid objects, there is a lack of tools that build rigged models of articulated objects that deform realistically using RGB-D data. We propose a method that creates a fully rigged model consisting of a watertight mesh, embedded skeleton and skinning weights by employing a combination of deformable mesh tracking, motion segmentation based on spectral clustering and skeletonization based on mean curvature flow.

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Thesis link (url) Project Page [BibTex]


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Evaluation of the passive dynamics of compliant legs with inertia

Györfi, B.

University of Applied Science Pforzheim, Germany, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation

Sücker, K.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

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[BibTex]

[BibTex]


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Understanding FORC using synthetic micro-structured systems with variable coupling- and coercivefield distributions

Groß, Felix

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

mms

[BibTex]


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Adsorption von Wasserstoffmolekülen in nanoporösen Gerüststrukturen

Kotzur, Nadine

Universität Stuttgart, Stuttgart, 2017 (mastersthesis)

mms

[BibTex]

[BibTex]

2005


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Extension to Kernel Dependency Estimation with Applications to Robotics

BakIr, G.

Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

Abstract
Kernel Dependency Estimation(KDE) is a novel technique which was designed to learn mappings between sets without making assumptions on the type of the involved input and output data. It learns the mapping in two stages. In a first step, it tries to estimate coordinates of a feature space representation of elements of the set by solving a high dimensional multivariate regression problem in feature space. Following this, it tries to reconstruct the original representation given the estimated coordinates. This thesis introduces various algorithmic extensions to both stages in KDE. One of the contributions of this thesis is to propose a novel linear regression algorithm that explores low-dimensional subspaces during learning. Furthermore various existing strategies for reconstructing patterns from feature maps involved in KDE are discussed and novel pre-image techniques are introduced. In particular, pre-image techniques for data-types that are of discrete nature such as graphs and strings are investigated. KDE is then explored in the context of robot pose imitation where the input is a an image with a human operator and the output is the robot articulated variables. Thus, using KDE, robot pose imitation is formulated as a regression problem.

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PDF PDF [BibTex]

2005


PDF PDF [BibTex]


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Geometrical aspects of statistical learning theory

Hein, M.

Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Implicit Surfaces For Modelling Human Heads

Steinke, F.

Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

ei

[BibTex]

[BibTex]


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Machine Learning Methods for Brain-Computer Interdaces

Lal, TN.

Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

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Web [BibTex]

Web [BibTex]


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Liver Perfusion using Level Set Methods

Nowozin, S.

Biologische Kybernetik, Shanghai JiaoTong University, Shanghai, China, July 2005 (diplomathesis)

ei

PDF [BibTex]

PDF [BibTex]


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Discriminative Methods for Label Sequence Learning

Altun, Y.

Brown University, Providence, RI, USA, May 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain

Tanner, TG.

Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

Abstract
A common task in psychophysics is to measure the psychometric function. A psychometric function can be described by its shape and four parameters: offset or threshold, slope or width, false alarm rate or chance level and miss or lapse rate. Depending on the parameters of interest some points on the psychometric function may be more informative than others. Adaptive methods attempt to place trials on the most informative points based on the data collected in previous trials. A new Bayesian adaptive psychometric method placing trials by minimising the expected entropy of the posterior probabilty dis- tribution over a set of possible stimuli is introduced. The method is more flexible, faster and at least as efficient as the established method (Kontsevich and Tyler, 1999). Comparably accurate (2dB) threshold and slope estimates can be obtained after about 30 and 500 trials, respectively. By using a dynamic termination criterion the efficiency can be further improved. The method can be applied to all experimental designs including yes/no designs and allows acquisition of any set of free parameters. By weighting the importance of parameters one can include nuisance parameters and adjust the relative expected errors. Use of nuisance parameters may lead to more accurate estimates than assuming a guessed fixed value. Block designs are supported and do not harm the performance if a sufficient number of trials are performed. The method was evaluated by computer simulations in which the role of parametric assumptions, its robustness, the quality of different point estimates, the effect of dynamic termination criteria and many other settings were investigated.

ei

[BibTex]

[BibTex]


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Support Vector Classification of Images with Local Features

Blaschko, MB.

Biologische Kybernetik, University of Massachusetts, Amherst, May 2005 (diplomathesis)

ei

[BibTex]

[BibTex]


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Adhesive microstructure and method of forming same

Fearing, R. S., Sitti, M.

March 2005, US Patent 6,872,439 (misc)

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[BibTex]

[BibTex]


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Event-Based Haptic Feedback

Kuchenbecker, K. J., Fiene, J. P., Niemeyer, G.

Hands-on demonstration at IEEE World Haptics Conference, Pisa, Italy, March 2005 (misc)

hi

[BibTex]

[BibTex]


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Efficient Pattern Selection for Support Vector Classifiers and its CRM Application

Shin, H.

Biologische Kybernetik, Seoul National University, Seoul, Korea, February 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Kernels: Regularization and Optimization

Ong, CS.

Biologische Kybernetik, The Australian National University, Canberra, Australia, 2005 (phdthesis)

ei

PDF GZIP [BibTex]

PDF GZIP [BibTex]


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Bruder sein das ist nicht schwer, Schwester sein dagegen sehr?" - Geschlechtsspezifische Betrachtungsweisen zur Situation von Geschwistern behinderter Kinder und Jugendlicher

Wirzberger, M.

Protestant University of Applied Sciences, Bochum, 2005 (thesis)

Abstract
Die Diplomarbeit beschäftigt sich mit der Lebenssituation von Geschwistern behinderter Kinder und Jugendlicher und berücksichtigt hier besonders den Aspekt des Geschlechts. Nach einer Darstellung familiensoziologischer Grundlagen erläutert die Verfasserin den hohen Stellenwert von Geschwisterbeziehungen innerhalb der Familie, sowie deren Entwicklung und Veränderung im Laufe des Lebens. Der Schwerpunkt liegt dabei auf dem Kindes- und Jugendalter. Anschließend werden Grundlagen, Prozesse und Mechanismen geschlechtsspezifischer Sozialisation, und die Auswirkungen des Geschlechts auf die Geschwisterbeziehung thematisiert. Kapitel 3 beschäftigt sich zunächst mit dem Begriff der Behinderung mit Bezug auf das SGB IX und die ICF. Danach beschreibt die Verfasserin, mit welchen spezifischen Belastungen sich die Eltern behinderter Kinder und Jugendlicher konfrontiert sehen. Die Auswirkungen einer Behinderung auf die Geschwister stehen im Mittelpunkt dieser Arbeit und werden anhand von Studien von HACKENBERG und GROSSMAN, sowie Aussagen von ACHILLES ausführlich dargestellt, wobei auch hier der Aspekt des Geschlechts detailliert in die Schilderung der Situation einbezogen wird. Um eine Verbindung von Theorie und Praxis zu gewährleisten, werden zusammenfassende Hypothesen formuliert und anhand von drei Fallgeschichten exemplarisch überprüft. Abschließend erläutert die Verfasserin die Konsequenzen ihrer Diplomarbeit für die heilpädagogische Arbeit.

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DOI [BibTex]


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Adaptation of Central Pattern Generators to Preexisting Mechanical Structure

Spröwitz, A.

Technische Universität Ilmenau, Ilmenau, 2005 (mastersthesis)

dlg

[BibTex]

[BibTex]


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Untersuchung über die Grenzflächenmagnetisierung an (FM) Kobalt- und (AFM) Eisen-Mangan-Schichten

Harlander, M.

Stuttgart, Universität Stuttgart, 2005 (mastersthesis)

mms

[BibTex]

[BibTex]