The amplitude of lower leg motor evoked potentials is a reliable measure when controlled for torque and motor task

Abstract : Objectives : Motor evoked potential (MEP) amplitudes have the disadvantage of a high variability when repeatedly assessed. This affects the reliability of MEP amplitude measurements taken during the course of motor incomplete spinal cord injury (iSCI). The study investigated the reliability of anterior tibial (TA) MEP measures controlled for dorsal flexion torque and motor task. Methods : TA MEPs were recorded at 10, 20, 40 and 60% of maximal voluntary contraction (MVC) during a static and dynamic (isometric increase of dorsal flexion torque) motor task. To determine reliability, 20 healthy and five chronic iSCI subjects were tested twice (≥7 days) by the same investigator. Intraclass correlation coefficients (ICCs) were calculated. MEP amplitudes and latencies were compared between 20 healthy and 29 iSCI subjects. Results : The reliability of MEP amplitude was in general good (ICC ≥ 0.52) and was highest during the static task at 40% MVC (ICC = 0.77). The increased facilitation by the dynamic motor task showed the best reliability at 20% MVC (ICC = 0.48). The reliability was good to excellent for MEP latency (0.46 ≥ ICC ≥ 0.81), MVC (ICC ≥ 0.90) and for the TMS threshold required to evoke a MEP response (ICC ≥ 0.77). The torque generated by the MEP response ()0.02 ≥ ICC ≥ 0.55) and the duration of the silent period (0.07 ≥ ICC ≥ 0.50) were not reliable. Both MEP amplitudes and latencies differed significantly between healthy and iSCI subjects. Conclusions : Controlling for torque generation and motor task establishes a reliability of TA MEP amplitudes that is sufficient for longitudinal assessments in motor incomplete SC

PI-Regler mit Anti-Windup für eine feldorientierte Motorregelung für ein Elektrofahrzeug

Die Arbeit wurde in Rahmen des europeischen StudentenAustauschprogramms ERASMUS am Institut ELSYS durchgeführt. Es geht um die Programmierung und Steuerung des Motors eines bereits vorhandenen Elektrofahrzeugs (E-Buggy). Für das Fahrzeug braucht man verschiedene Komponenten, wie einen Umrichter der von einem Mikrocontroller gesteuert und geregelt wird, andere Leistungselektronik Elemente, sowie ein kleines Batteriemanagement

UltraZohm - An Open-Source Rapid Control Prototyping Platform for Power Electronic Systems

This paper presents two rapid control prototyping (RCP) use cases facilitated by the open-source platform UltraZohm. The openly available UltraZohm development framework eases the transition from simulation to the test bench. The framework offers the integration of automatic code generation for field-programmable gate arrays (FPGAs), either by using Simulink models based on the HDL Coder, or by synthesizing C++ code into VHDL via the Vivado high-level synthesis tool. The first use case focuses on the implementation details of an on-chip controller-in-the-loop setup, where a permanent magnet synchronous machine is emulated in the FPGA with a sampling frequency of 2 MHz. The second use case presents an efficient real-time implementation of the sphere decoding algorithm employed to solve the long-horizon finite control set model predictive control problem for a three-level neutral point clamped inverter driving an induction machine. Experimental results based on a small-scale prototype confirm that the algorithm can be executed in real time on the FPGA, with an execution time of a few tens of microseconds. Both use cases highlight the benefits of using a high-performance RCP platform for research in power electronics and their control.acceptedVersionPeer reviewe

Variable Switching Point Predictive Current Control for Multi-Phase Permanent Magnet Synchronous Drives

Finite control set model predictive control (FCS-MPC) is a promising method for the control of multi-phase machines, due to its capability to directly account for nonlinearities and multiple controlled variables. To overcome the drawback of high current ripples and excitation of harmonic currents in the so-called xy-subsystem, several methods have been proposed in the literature so far. This paper proposes an MPC-based method that achieves high granularity of switching by not only switching at the discrete time steps, but also within the sampling interval. In doing so, the discussed algorithm, referred to as variable switching point current control (VSP2CC), produces low current distortions, while still keeping the advantages of conventional FCS-MPC, such as fast dynamic behavior during transients. To highlight the above, VSP2CC is applied to a six-phase permanent magnet synchronous machine (PMSM) and compared with conventional FCS-MPC and MPC that employs virtual voltage vectors (VV-MPC).acceptedVersionPeer reviewe

Deep Reinforcement Learning Current Control of Permanent Magnet Synchronous Machines

This paper presents a current control approach for permanent magnet synchronous machines (PMSMs) using the deep reinforcement learning algorithm deep deterministic policy gradient (DDPG). The proposed method is designed by examining different training setups regarding the reward function, the observation vector, and the actor neural network. In doing so, the impact of the different design factors on the steady-state and dynamic behavior of the system is assessed, thus facilitating the selection of the setup that results in the most favorable performance. Moreover, to provide the necessary insight into the controller design, the entire path from training the agent in simulation, through testing the control in a controller-in-the-loop (CIL) environment, to deployment on the test bench is described. Subsequently, experimental results are provided, which show the efficacy of the presented algorithm over a wide range of operating points. Finally, in an attempt to promote open science and expedite the use of deep reinforcement learning in power electronic systems, the trained agents, including the CIL model, are rendered openly available and accessible such that reproducibility of the presented approach is possible.Peer reviewe

Both systemic and local application of Granulocyte-colony stimulating factor (G-CSF) is neuroprotective after retinal ganglion cell axotomy

<p>Abstract</p> <p>Background</p> <p>The hematopoietic Granulocyte-Colony Stimulating Factor (G-CSF) plays a crucial role in controlling the number of neutrophil progenitor cells. Its function is mediated via the G-CSF receptor, which was recently found to be expressed also in the central nervous system. In addition, G-CSF provided neuroprotection in models of neuronal cell death. Here we used the retinal ganglion cell (RGC) axotomy model to compare effects of local and systemic application of neuroprotective molecules.</p> <p>Results</p> <p>We found that the <it>G-CSF receptor </it>is robustly expressed by RGCs <it>in vivo </it>and <it>in vitro</it>. We thus evaluated G-CSF as a neuroprotectant for RGCs and found a dose-dependent neuroprotective effect of G-CSF on axotomized RGCs when given subcutaneously. As stem stell mobilization had previously been discussed as a possible contributor to the neuroprotective effects of G-CSF, we compared the local treatment of RGCs by injection of G-CSF into the vitreous body with systemic delivery by subcutaneous application. Both routes of application reduced retinal ganglion cell death to a comparable extent. Moreover, G-CSF enhanced the survival of immunopurified RGCs <it>in vitro</it>.</p> <p>Conclusion</p> <p>We thus show that G-CSF neuroprotection is at least partially independent of potential systemic effects and provide further evidence that the clinically applicable G-CSF could become a treatment option for both neurodegenerative diseases and glaucoma.</p

Modular Mechatronics Infrastructure for Robotic Planetary Exploration Assets in a Field Operation Scenario

In 2021 the Modular Mechatronics Infrastructure (MMI) was introduced as a solution to reduce weight, costs, and development time in robotic lanetary missions. With standardized interfaces and multi-functional elements, this modular approach is planned to be used more often in sustainable exploration activities on the Moon and Mars. The German multi-robot research project “Autonomous Robotic Networks to Help Modern Societies (ARCHES)” has explored this concept with the use of various collaborative robotic assets which have their capabilities extended by the MMI. Different scientific payloads, engineering infrastructure modules, and specific purpose tools can be integrated to and manipulated by a robotic arm and a standardized electromechanical docking-interface. Throughout the MMI’s design and implementation phase the performed preliminary tests confirmed that the different systems of the robotic cooperative team such as the Docking Interface System (DIS), the Power Management System (PMS), and the Data Communication System (DCS) functioned successfully. During the summer of 2022 a Demonstration Mission on Mount Etna (Sicily, Italy) was carried out as part of the ARCHES Project. This field scenario allowed the validation of the robotics systems in an analogue harsh environment and the confirmation of enhanced operations with the application of this modular method. Among the numerous activities performed in this volcanic terrain there are the efficient assembling of the Low Frequency Array (LOFAR) network, the energy-saving and reduced complexity of a detached Laser Induced Breakdown Spectroscopy (LIBS) module, and the uninterrupted powered operation between modules when switching between different power sources. The field data collected during this analogue campaign provided important outcomes for the modular robotics application. Modular and autonomous robots certainly benefit from their versatility, reusability, less complex systems, reduced requirements for space qualification, and lower risks for the mission. These characteristics will ensure that long duration and complex robotic planetary endeavours are not as challenging as they used to be in the past

Reinforcement Learning Control of Six-Phase Permanent Magnet Synchronous Machines

Control of multi-phase machines is a challenging topic due to the high number of controlled variables. Conventional control methods, such as field-oriented control (FOC), address this issue by introducing more control loops. This, however, increases the controller design complexity, while the tuning process can become cumbersome. To tackle the above, this paper proposes a deep deterministic policy gradient algorithm based controller that fulfills all the control objectives in one computational stage. More specifically, the proposed approach aims to learn a suitable current control policy for six-phase permanent magnet synchronous machines to simplify the commissioning of the drive system. In doing so, physical limitations of the drive system can be accounted for, while the compensation of imbalances between the two three-phase subsystems is rendered possible. After validating the training results in a controller-in-the-loop environment, test bench measurements are provided to demonstrate the effectiveness of the proposed controller. As shown, favorable steady-state and dynamic performance is achieved that is comparable to that of FOC. Therefore, as indicated by the presented results, reinforcement learning-based control approaches for multi-phase machines is a promising research area.Peer reviewe

Robotische Hernienchirurgie I

The treatment of inguinal hernias with open and minimally invasive procedures has reached a high standard in terms of outcome over the past 30 years. However, there is still need for further improvement, mainly in terms of reduction of postoperative seroma, chronic pain, and recurrence. This video article presents the endoscopic anatomy of the groin with regard to robotic transabdominal preperitoneal patch plasty (r‑TAPP) and illustrates the surgical steps of r‑TAPP with respective video sequences. The results of a cohort study of 302 consecutive hernias operated by r‑TAPP are presented and discussed in light of the added value of the robotic technique, including advantages for surgical training. r‑TAPP is the natural evolution of conventional TAPP and has the potential to become a new standard as equipment availability increases and material costs decrease. Future studies will also have to refine the multifaceted added value of r‑TAPP with new parameters

Design and Implementation of a Modular Mechatronics Infrastructure for Robotic Planetary Exploration Assets

Traditionally, the robotic systems which aim to explore other celestial bodies include all instruments and tools necessary for the mission. This makes them unique developments. Usually, they are heavy, complex, costly and do not provide any interchangeable parts that could be replaced in the event of permanent failure. However, for future missions, agencies, institutes and commercial companies are developing robotics systems based on the concept of modular robotics. This new strategy becomes critical for planetary exploration because it is able to reduce load, costs and development time. In the German multi robot research project, ‘’Autonomous Robotic Networks to Help Modern Societies (ARCHES)”, led by the German Aerospace Center (DLR), this modern design methodology is followed. Cooperation among robots and modularity are the core of its structure. These characteristics are present in the collaboration between the rovers and the uncrewed aerial vehicle (UAV) during navigation tasks, or when the Lightweight Rover Unit (LRU) interacts with changeable manipulator tools and payload boxes through its robotic arm and its standardized electromechanical interface. Examples of these modules include scientific packages, power supply systems, communication and data acquisition architectures, soil sample storage units, and specific purpose end-effectors. The focus of this work is in the design and implementation of a mechatronics infrastructure (MI) which encompasses the docking interface, the payload modules, and the power and data management electronics board inside each box. These three elements are essential for the extension of the capabilities of the rover and the enhancement of the robotics systems according to the tasks to be performed. This will ensure that robots can cooperate with each other either in scientific missions or in the construction and maintenance of large structures. The MI’s hardware and software developed in this project will be tested and validated in the ARCHES demonstration mission on Mount Etna, Sicily, in Italy between 13th June and 9th July 2022. Finally, it is important to highlight that modularity and standardization were considered at all levels of the infrastructure. From the robotics systems to the internal architecture of each payload module, these concepts can provide versatility and reliability to the cooperative robotic network. This will improve the problem-solving capabilities of robots performing complex tasks in future planetary exploration missions