Heiko Maass

A Prospective Randomized Study to Test the Transfer of Basic Psychomotor Skills From Virtual Reality to Physical Reality in a Comparable Training Setting

Objective:To test whether basic skills acquired on a virtual endoscopic surgery simulator are transferable from virtual reality to physical reality in a comparable training setting. Summary Background Data:For surgical training in laparoscopic surgery, new training methods have to be developed that allow surgeons to first practice in a simulated setting before operating on real patients. A virtual endoscopic surgery trainer (VEST) has been developed within the framework of a joint project. Because of principal limitations of simulation techniques, it is essential to know whether training with this simulator is comparable to conventional training. Methods:Devices used were the VEST system and a conventional video trainer (CVT). Two basic training tasks were constructed identically (a) as virtual tasks and (b) as mechanical models for the CVT. Test persons were divided into 2 groups each consisting of 12 novices and 4 experts. Each group carried out a defined training program over the course of 4 consecutive days on the VEST or the CVT, respectively. To test the transfer of skills, the groups switched devices on the 5th day. The main parameter was task completion time. Results:The novices in both groups showed similar learning curves. The mean task completion times decreased significantly over the 4 training days of the study. The task completion times for the control task on Day 5 were significantly lower than on Days 1 and 2. The experts’ task completion times were much lower than those of the novices. Conclusions:This study showed that training with a computer simulator, just as with the CVT, resulted in a reproducible training effect. The control task showed that skills learned in virtual reality are transferable to the physical reality of a CVT. The fact that the experts showed little improvement demonstrates that the simulation trains surgeons in basic laparoscopic skills learned in years of practice.

Impact of sleep deprivation on medium-term psychomotor and cognitive performance of surgeons: prospective cross-over study with a virtual surgery simulator and psychometric tests.

BACKGROUND Despite recent work hour restrictions, 24-hour calls remain an important part of patient care. The aim of this study was to assess the impact of 24-hour night calls on the psychomotor and cognitive skills of surgeons with a virtual surgery simulator (VSS) and psychometric tests. We hypothesized that sleep loss impairs surgical skills and concentration performance. METHODS Seventeen surgery residents (test group) and 13 medical students (reference group) performed a 5-day training program on the VSS. The test group was then assessed during a night call on 4 test points (8 am and 4 pm on the on-call day, 8 am on the postcall day, and 8 am on the recovery day) to assess the effects of sleep loss on these surgery residents. The reference group performed the same tests but without a night call. RESULTS The training resulted in a homogenous performance level for both groups. The average time for the test group was 26 minutes. The analysis between rested and sleep-deprived participants (6.5 +/- 0.9 vs 2.9 +/- 1.4 hours of night sleep) in the on-call part showed no performance differences. No impairment was found for the VSS and the cognitive tests within the test group between the start of the working day and the start of the postcall day after the night of relative sleep loss. The subgroup analysis showed no significant differences regarding the amount of night sleep and laparoscopic experience. CONCLUSION No performance impairment was found for surgeons with a VSS and standardized cognitive tests after a night of relative sleep loss. Although there is no doubt that sleep deprivation ultimately impairs human functioning, typical surgical skills do not necessarily deteriorate with a limited amount of sleep loss under clinical conditions.

Fundamentals of Force Feedback and Application to a Surgery Simulator

Force feedback increases the effectiveness of virtual-reality surgery training systems. An overview of the fundamentals of applying force feedback is presented. An impedance control technique and data processing methods for stability preservation are illustrated. A flexible interface for general force-feedback applications has been developed. This interface is capable of controlling several different force-feedback hardware systems, including the SensAble PHANTOM, the Laparoscopic Impulse Engines from Immersion, and the VS-One virtual endoscopic surgery trainer. The findings are evaluated using the main simulation system, KISMET, and the modeling tools KISMO and VESUV. Within the scope of a cooperative project called HapticIO (funded by the German Ministry of Education and Research [BMBF]), new haptic devices have been designed for virtual neuroendoscopy and laparoscopy. The concept and implementations presented in this paper have been found to be flexible, stable and suitable for universal use. The impedance method, combined with the open-loop feed-forward control technique, is well suited and appropriate for the task.

Power Grid Time Series Data Analysis with Pig on a Hadoop Cluster Compared to Multi Core Systems

In order to understand the dependencies in the power system we try to derive state information by combining high-rate voltage time series captures at different locations together with data analysis at different scales. This may enable large-scale simulation and modeling of the grid. Data captured by our recently introduced Electrical Data Recorders (EDR) and power grid simulation data are stored in the large scale data facility (LSDF) at Karlsruhe Institute of Technology (KIT) and growing rapidly in size. In this article we compare classic sequential multithreaded time series data processing to a distributed processing using Pig on a Hadoop cluster. Further we present our ideas for a better organization for our raw- and metadata that is indexable, searchable and suitable for big data.

A Virtual-Reality-Based Haptic Surgical Training System

To improve training facilities for surgeons, a surgical training system based on virtual reality techniques has been developed. The goal of the developed system is to improve education of surgeons by making the knowledge of expert surgeons directly available to trainees. The system realizes two different approaches: the library and the driving school paradigm. In its current form, the system consists of two modules. The main module combines the virtual reality kernel KISMET, a visual and haptic display, and a database of different operations and/or techniques. The master station is a copy of the input and output facilities of the main module. Both modules communicate by a TCP/IP-based connection. Initial tests demonstrated the feasibility of the chosen framework. Further developments include the gathering of data not only from virtual reality but also from real operations. Robotic-assisted surgery provides an attractive way of accomplishing this.

First Evaluation Results Using the New Electrical Data Recorder for Power Grid Analysis

Today, power systems are subject to fundamental changes concerning functionality and dynamics due to new energy sources and increasing demand. However, detailed information of the system and the system state is the property of the suppliers or distributors, and is not comprehensively available to researchers at present. We propose to capture easily accessible, high-rate, low-voltage (LV) time series at different locations, and to store the whole data for subsequent usage in a large database. A system state simulation shall use these data and provide for load information without knowing the currents. For this purpose, we develop the electrical data recorder (EDR) and perform measurements in our first starting test site, the island network like Karlsruhe Institute of Technology campus. We first present comparison results between captured voltage characteristics and campus smart meter measurements that we use as an indication of the load status. We develop the Electrical Grid Analysis Simulation Modeling and Visualization Tool (eASiMoV) and show feasibility in a simple simulation. We measure the storage transfer to the large-scale database facility and give evaluation results. The EDR device, the eASiMoV software, and data handling methods are exhibited as valuable components of a promising new approach.

Introducing the Electrical Data Recorder as a new capturing device for power grid analysis

Power systems are facing fundamental changes concerning functionality and dynamics today. However, detailed data of the system are property of the suppliers or distributors and are not easily available to researchers at present. In order to understand the system dependencies we propose to derive state information by combining high-rate low-voltage time series captures at different locations together with a simulation model of the grid. We take the island network like KIT campus as our starting investigation site. In a first step we developed the Electrical Data Recorder (EDR), which is capable of recording three phase voltage time series at up to 25 kHz synchronously. All data are stored in a large scale database facility (LSDF) for subsequent usage. We intend to derive a simulation model from the comparison of the voltage characteristics to periodic smart meter measurements as the indication of the load status. In this article we introduce the new recording device and present first results.

Ein Ansatz zur automatisierten Erstellung umfangreicher und komplexer Simulationsmodelle für elektrische Übertragungsnetze aus OpenStreetMap-Daten

Zusammenfassung Lastfluss-Simulationen in Stromnetzen stellen die Grundlage für regelungstechnische Analysen dar, auch und gerade für Smart Grids der Zukunft. Die Generierung und die Verwaltung von komplexen und umfangreichen Stromnetzmodellen mit Berücksichtigung variabler regionaler Modellgranularität ist eine große Herausforderung, zumal die manuelle Erstellung aufgrund der enormen Datenmenge sehr schwer durchzuführen ist. Im vorliegenden Beitrag wird ein Ansatz zur automatisierten Generierung von Stromnetzmodellen ausschließlich aus OpenStreetMap-Daten, frei verfügbaren öffentlichen und amtlichen Datenbanken sowie Geo-Webdiensten vorgestellt. Eine neue Methode zur Generierung von dynamischen Lasten basierend auf Voronoi-Geopartitionierung unter Berücksichtigung der Netztopologie wird zudem ausgearbeitet. Ein erstes, voll automatisiert erstelltes Stromnetzmodell für das Übertragungsnetz in Baden-Württemberg wird mit dynamischer Lastflusssimulation evaluiert.

One year high rate low voltage recording - Devices, methods and results

Power system management currently advances from rigid to flexible and requires highly sophisticated monitoring and control in the future. In order to contribute to a more detailed analysis and to provide a fundamental database for simulation and investigation we developed the recording device EDR (Electrical Data Recorder). Synchronized continuous high rate captures of low voltage time series are stored in a central database without any data reduction. Since more than one year we already record voltage transient information from the KIT campus power supply. We checked the device for accuracy, for reliability and developed methods for large scale data storage and for use with simulation. In this paper we present these devices and methods, as well the improvements, derived from the experiences we gathered in our studies. We conclude that the EDR provides high accuracy and precision; our data storage and retrieval methods are fast and appropriate; but available simulation tools need improvements. The system is now ready for productive use in the low voltage supply grid.

Preparing the electrical data recorder for comparative power network measurements

As the power system management currently advances from rigid to flexible, highly sophisticated monitoring and control is required in the future. By developing the Electrical Data Recorder (EDR) and preparing the device for comparative tests in low voltage power network at multiple locations we intend to contribute to a more detailed analysis and to provide a fundamental database for simulation and investigation. Using EDR devices, high rate captures of low voltage time series are acquired synchronously and are stored in a central large database without any information reduction. We performed extensive tests according to the IEC 61000-4-30 standard in order to assure the comparability of the measured values. Special attention was paid to the synchronization for achieving temporal coincidence of values measured at different locations. We developed methods for large scale data storage and interfaces for 3rd party simulation packages. In this paper we present the preparation of the device and the test procedures as well as the results. We report on the methods we already provide for data management and analysis. We conclude that the EDR provides sufficient accuracy and precision for comparative tests; our data storage and retrieval methods are fast and reliable; and we did not find 3rd party simulation tools appropriate for our needs, yet. However, the measurement system is ready for productive use in the low voltage supply grid.