Heiko Maaß

Endoscopic surgery training using virtual reality and deformable tissue simulation

Abstract Surgical training systems based on virtual reality (VR) and simulation techniques for tissue deformation may represent a more cost-effective and efficient alternative to traditional training methods. Additionally, VR is a technology that can teach surgeons new procedures and can determine their level of competence before they operate on patients. At Forschungszentrum Karlsruhe (FZK), a virtual reality training system for minimally invasive surgery (MIS), based on the simulation software KISMET, has been developed. An overview of the current state of development for the “Karlsruhe Endoscopic Surgery Trainer” is presented. For quick and easy creation of surgical scenes containing deformable anatomical organ models, the spline-based modeller KisMo has been developed, which generates beside the geometry also a spatial mass–spring network of the objects for the elastodynamic simulation in KISMET. The MIS trainer provides several surgical interaction modules for deformable objects like grasping, application of clips, cutting, coagulation, injection and suturing. Additionally, it is possible to perform irrigation and suction in the operation area. Active deformable objects are used for the morphodynamic simulation of the stomach and the intestines. Furthermore, a hierarchical pulse simulation in virtual arterial vessel trees has been realized, which enables the palpation of the pulse with a force-feedback device. The pulse simulation is coupled with an arterial bleeding simulation, which gets activated by injuries of arteries and stopped by application of clips. The simulation system has been applied to minimally invasive surgery training in gynaecology and laparoscopy. Special attention is addressed to elastodynamically deformable tissue models and geometric modelling techniques for graphical real-time performance.

An augmented reality home-training system based on the mirror training and imagery approach

Mirror training and movement imagery have been demonstrated to be effective in treating several clinical conditions, such as phantom limb pain, stroke-induced hemiparesis, and complex regional pain syndrome. This article presents an augmented reality home-training system based on the mirror and imagery treatment approaches for hand training. A head-mounted display equipped with cameras captures one hand held in front of the body, mirrors this hand, and displays it in real time in a set of four different training tasks: (1) flexing fingers in a predefined sequence, (2) moving the hand into a posture fitting into a silhouette template, (3) driving a “Snake” video game with the index finger, and (4) grasping and moving a virtual ball. The system records task performance and transfers these data to a central server via the Internet, allowing monitoring of training progress. We evaluated the system by having 7 healthy participants train with it over the course of ten sessions of 15-min duration. No technical problems emerged during this time. Performance indicators showed that the system achieves a good balance between relatively easy and more challenging tasks and that participants improved significantly over the training sessions. This suggests that the system is well suited to maintain motivation in patients, especially when it is used for a prolonged period of time.

The Importance of Synchrony and Temporal Order of Visual and Tactile Input for Illusory Limb Ownership Experiences – An fMRI Study Applying Virtual Reality

In the so-called rubber hand illusion, synchronous visuotactile stimulation of a visible rubber hand together with ones own hidden hand elicits ownership experiences for the artificial limb. Recently, advanced virtual reality setups were developed to induce a virtual hand illusion (VHI). Here, we present functional imaging data from a sample of 25 healthy participants using a new device to induce the VHI in the environment of a magnetic resonance imaging (MRI) system. In order to evaluate the neuronal robustness of the illusion, we varied the degree of synchrony between visual and tactile events in five steps: in two conditions, the tactile stimulation was applied prior to visual stimulation (asynchrony of −300 ms or −600 ms), whereas in another two conditions, the tactile stimulation was applied after visual stimulation (asynchrony of +300 ms or +600 ms). In the fifth condition, tactile and visual stimulation was applied synchronously. On a subjective level, the VHI was successfully induced by synchronous visuotactile stimulation. Asynchronies between visual and tactile input of ±300 ms did not significantly diminish the vividness of illusion, whereas asynchronies of ±600 ms did. The temporal order of visual and tactile stimulation had no effect on VHI vividness. Conjunction analyses of functional MRI data across all conditions revealed significant activation in bilateral ventral premotor cortex (PMv). Further characteristic activation patterns included bilateral activity in the motion-sensitive medial superior temporal area as well as in the bilateral Rolandic operculum, suggesting their involvement in the processing of bodily awareness through the integration of visual and tactile events. A comparison of the VHI-inducing conditions with asynchronous control conditions of ±600 ms yielded significant PMv activity only contralateral to the stimulation site. These results underline the temporal limits of the induction of limb ownership related to multisensory body-related input.

Data processing of high-rate low-voltage distribution grid recordings for smart grid monitoring and analysis

Power networks will change from a rigid hierarchic architecture to dynamic interconnected smart grids. In traditional power grids, the frequency is the controlled quantity to maintain supply and load power balance. Thereby, high rotating mass inertia ensures for stability. In the future, system stability will have to rely more on real-time measurements and sophisticated control, especially when integrating fluctuating renewable power sources or high-load consumers like electrical vehicles to the low-voltage distribution grid.In the present contribution, we describe a data processing network for the in-house developed low-voltage, high-rate measurement devices called electrical data recorder (EDR). These capture units are capable of sending the full high-rate acquisition data for permanent storage in a large-scale database. The EDR network is specifically designed to serve for reliable and secured transport of large data, live performance monitoring, and deep data mining. We integrate dedicated different interfaces for statistical evaluation, big data queries, comparative analysis, and data integrity tests in order to provide a wide range of useful post-processing methods for smart grid analysis.We implemented the developed EDR network architecture for high-rate measurement data processing and management at different locations in the power grid of our Institute. The system runs stable and successfully collects data since several years. The results of the implemented evaluation functionalities show the feasibility of the implemented methods for signal processing, in view of enhanced smart grid operation.

Vision-based Hand Representation and Intuitive Virtual Object Manipulation in Mixed Reality

In this paper we introduce a method for representation of the human hand in virtual or mixed environments and interaction with virtual objects. We use a head-mounted display with two cameras installed on top to record the user s hand, which is then cut out and shown in the virtual environment. Extracted features like silhouette and fingertip positions enable direct visual interaction with objects in virtual worlds. Applications of the approach are presented and feature extraction methods, the overlay technique and the hardwareand software setup of the system are described. Finally the benefits and limitations of the approach are discussed.

Illusory Hand Ownership Induced by an MRI Compatible Immersive Virtual Reality Device

In this paper, we introduce a virtual reality based setup for triggering and studying illusory sensations of limb ownership as known from the popular rubber hand illusion. Unlike a similar setup introduced recently, this experiment is triggered by software automatically, which provides for a good synchrony and for high accuracy of visuotactile stimulation. The system is usable inside a magnetic resonance scanner which allows observing cortical activations at the same time. We tested two participants, one highly and the other lowly susceptible to the induction of illusory limb ownership, assessing their subjective experiences as well as their brain activity using functional magnetic resonance imaging. We present preliminary results suggesting that our setup induces illusory ownership experiences for a virtual limb successfully, accompanied by neuronal activation in integrative brain areas.

Security in Large-Scale Data Management and Distributed Data Acquisition

The internet is about to change from a pure network of computers to a network of more or less intelligent devices, the computer being just one of them. Examples of this change are the concepts of smart applications like smart homes, smart traffic control and guidance systems, smart power grids, or smart buildings. These systems require among others a high degree of robustness, reliability, scalability, safety, and security. In this paper, we concentrate on the data exchange and management aspect and introduce a security concept for scalable and easy-to-use Generic Data Services, called SeGDS. It covers application scenarios from embedded field devices for data acquisition to large-scale generic data applications and data management. The concept is based largely on proven standard enterprise hardware and standard solutions. As a first application, we report about transport and management of mass data originating from high-resolution electrical data devices, which measure parameters of the electrical grid with a high sample rate. The shown solution is intended to be a contribution to concepts of a secure, flexible, but comparably inexpensive management of large amounts of data coming from modern smart power grids or other comparable smart applications.

Comparison of lossless compression schemes for high rate electrical grid time series for smart grid monitoring and analysis

Abstract The smart power grid of the future will utilize waveform level monitoring with sampling rates in the kilohertz range for detailed grid status assessment. To this end, we address the challenge of handling large raw data amount with its quasi-periodical characteristic via lossless compression. We compare different freely available algorithms and implementations with regard to compression ratio, computation time and working principle to find the most suitable compression strategy for this type of data. Algorithms from the audio domain (ALAC, ALS, APE, FLAC & TrueAudio) and general archiving schemes (LZMA, Delfate, PPMd, BZip2 & Gzip) are tested against each other. We assemble a dataset from openly available sources (UK-DALE, MIT-REDD, EDR) and establish dataset independent comparison criteria. This combination is a first detailed open benchmark to support the development of tailored lossless compression schemes and a decision support for researchers facing data intensive smart grid measurements.

Poster abstract: graph-theoretic model for observability in multi-carrier energy distribution networks

The increasing installation of decentralized energy converters merges networks of different energy carriers to a multi-carrier energy distribution network (MEDN). To operate MEDNs efficiently and safe, the state of the network has to be monitored. An economically reasonable approach for monitoring MEDNs is provided by state estimation techniques, which however expect the network to be observable. To the best of our knowledge, we are the first to address the observability on MEDNs. Hence, we introduce a first graph-theoretic model serving as a starting point for introducing structural concepts, such as observability, for MEDNs.

Security Issues in Distributed Data Acquisition and Management of Large Data Volumes

The internet is faced with new application scenarios like smart homes, smart traffic control and guidance systems, smart power grids, or smart buildings. They all have in common that they require a high degree of robustness, reliability, scalability, safety, and security. This paper provides a list of criteria for these properties and focuses on the aspect of data exchange and management. It introduces a security concept for scalable and easy-to-use Secure Generic Data Services, called SeGDS, which covers application scenarios extending from embedded field devices for data acquisition to large-scale generic data applications and data management. Our concept is based largely on proven standard solutions and uses standard enterprise hardware. The first application deals with transport and management of mass data originating from high-resolution electrical data devices, which measure parameters of the electrical grid with a high sample rate.